Page 3 – DataToBiz

Yashica Chopra
January 16, 2025
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AI as a Service (AIaaS) Providers for 2025 : Top 20 Picks

Artificial intelligence can be a cloud-based service through the AIaaS business model. This allows every business to adopt advanced technologies. Here, we’ll discuss the top twenty AI as a Service provider to look for in 2025. Artificial intelligence services have been in high demand in recent years. With technological advancements hitting the markets regularly, businesses need to adapt to the changes quickly. This led to AI as a service business model where offshore service providers offer end-to-end AI solutions remotely through cloud platforms. According to Research and Markets, the global AI as a Service market is likely to be $24.947 billion in 2024 and is projected to reach $168.449 billion by 2029 at a CAGR (compound annual growth rate) of 46.52%. Also called AIaaS, the service model allows enterprises to build, deploy, and integrate low-cost cloud-based AI apps to streamline various business activities and increase ROI. In this blog, we’ll look at the top twenty AI as a Service providers worldwide and explore their services. It is recommended to hire a company that has expertise in your industry and can align the solutions with your long-term objectives. 20 Top AI as a Service Providers in 2025 DataToBiz DataToBiz is an end-to-end AI product development company offering a plethora of services to help startups, SMBs, MSMEs, and large enterprises adopt new technologies. The company is a certified partner of Microsoft (Gold), Google, and AWS. It has a presence in many countries and works with businesses to create future-proof systems with greater scalability. The company’s AI as a service solutions are client-centric and provide measurable results. Businesses can achieve sustainable growth by unlocking their full potential through their partnership with DataToBiz. As an award-winning company, it also has various certifications for data security, and data privacy, and is compliant with global regulations. The company follows a tried and tested multi-step approach to guide the client from ideation to implementation and provides long-term maintenance and support services. STX Next STX Next is a global IT consulting company offering an array of advanced technologies and AI-powered solutions. The company transforms businesses with AI and ML services to enhance automation, reduce downtime, and promote data-driven decision-making. It combines retrieval and generation models to provide RAG as a service, which results in powerful chatbots that can deliver accurate results. The company has expert professionals with years of experience and is accustomed to tackling complex business challenges on behalf of clients. STX Next builds custom AI apps to suit the budget, industry, and business-specific needs of clients from diverse sectors. It has a reliable partner ecosystem to leverage advanced AI capabilities and help enterprises deliver greater value to their customers. IndiaNIC IndiaNIC is an IT company with a global presence. It is a family-filled service provider with startups, mid-sized businesses, enterprises, and multinational brands as clients. The company offers innovative AI product development services to accelerate growth and help clients adopt cutting-edge technologies for cost-effective prices. It offers a range of AI solutions like custom development, ML development, generative AI, NLP, and more. The company optimizes business operations using AI technologies to automate repetitive tasks, deliver reliable predictive analytics, and support data-driven decisions. IndiaNIC plays a key role in assisting enterprises to grab market opportunities and improve customer experiences. The expert professionals work with a plethora of AI technologies to deliver tailored solutions as per each client’s requirements. Ekkel AI Ekkel Inc. is an AI services company offering professional, personalized, and powerful tech solutions. It provides staff augmentation services for businesses worldwide to hire vetted teams to build advanced AI models and implement them in their enterprises. The company follows a result-driven approach and uses versatile technologies to deliver the promised results. It helps clients build powerful and customized AI products for web and mobile platforms. Ekkel Inc. also offers machine learning consulting services to assist data scientists in using dependable models for deriving actionable insights from large datasets. The company’s AI transformation service is aimed at helping businesses identify growth opportunities and adopt the right artificial intelligence tools to achieve their goals. Softude Softude is a business transformation company and digital implementation specialist working with diverse clients to help them convert their digital dreams into reality. The company is also an AI as a Service provider with experienced professionals to guide businesses to harness the power of artificial intelligence. It takes care of the resources, expertise, and other aspects so that every business, irrespective of its size and abilities, can adopt new technologies and survive market competition. Softude builds, deploys, and launches various AI products on cloud platforms and uses APIs to set up seamless third-party integrations between different systems. The company’s private deployment service ensures that the AI apps are hosted on secure servers and cannot be accessed by others. It is an ISO-certified company and has won many awards. ServiceNow ServiceNow is an innovative AI company offering artificial intelligence-enabled platforms to businesses from various regions and industries. It provides AIaaS solutions and generative AI services to encourage business transformation and help people work smarter. ITheNow Platform® is a purpose-driven solution that can be quickly deployed to streamline workflows. The company specializes in delivering actionable AI tools to enterprises and helps them implement the solutions across all departments and verticals. ServiceNow also has pre-built AI solutions for all use cases. These can be customized as per the client’s needs and integrated with other tools to optimize operations and enhance productivity. The company prioritizes data security and keeps the business data safe from unauthorized access. Quytech Quytech is an AI product development company offering bespoke services for startups and enterprises alike. It builds future-proof and feature-rich mobile apps, software solutions, and more based on client’s requirements. The company’s suite of AI services is designed to guide businesses at various growth stages streamline their processes and achieve their goals. From AI consulting to AI as a Service, AI security, and predictive analytics, the company offers customized solutions to align with each business. Quytech also offers generative AI

Yashica Chopra
January 15, 2025
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Inhouse vs Outsourced RCM Analytics – The Ideal Choice in Healthcare?

Revenue cycle management (RCM) is managing patient data, claims, and payments from start to finish. Here, we’ll discuss the role of RCM analytics in healthcare and determine the differences between in-house and outsourced analytics services. The healthcare industry deals with many administrative and financial tasks. From patient applications to transactions with insurance companies, the processes can be complex and time-consuming. This is one of the reasons why billing takes so much time in hospitals, causing more delays and frustration for the administrators and patients. Fortunately, RCM provides an effective solution for this. To improve things, RCM analytics identifies the root cause of delays and helps streamline the entire process. But what is RCM? What does RCM stand for? RCM is Revenue Cycle Management, the process of identifying, collecting, and managing payments from patients of the healthcare center. It is necessary for patient management and financial management. The RCM market is expected to grow at a CAGR of 12.2% between 2025 and 2032 to reach $342.6 billion by 2032. Revenue cycle management (RCM) software streamlines and automates revenue cycle management. So, what is RCM software, and how does it work? RCM software is similar to medical billing software that tracks the patient’s case from initial registration to discharge. It is used to calculate the final payment, insurance payouts, etc. It also maintains a proper record of each patient with ID. However, healthcare establishments face many problems in medical billing and RCM. RCM analytics provides a reliable solution for these issues. But should a hospital opt for in-house billing or outsource the task? Let’s find answers to these questions and more! RCM Challenges in Healthcare Before we explore the differences between how in-house RCM and outsourced analytics work, let’s first understand the challenges of healthcare RCM analytics. Human Error The hospital staff is often overworked and stressed due to the extensive responsibilities they handle. By asking them to manually manage patient registrations and payments, there’s a high risk of human error or a wrong entry. Complex Process The roles and responsibilities of front-end and back-end employees are different. RCM has to effectively bridge the gap to minimize confusion, incorrect information, delays, etc. The process is just too complex and stressful without using the latest technology. Missing and Outdated Data With the administration fragmented into individual departments, there’s a risk of patient data missing from files. For example, if someone forgets to mention the information about the patient’s insurance in a report, it could lead to a series of confusion and miscommunication. RCM data management through modern data warehousing services can solve this problem. Changing Regulations The regulations in the healthcare and insurance industries can change, resulting in confusion among patients and administrative departments. It could be something as simple as a hospital not having a tie-up with a certain insurer, leading to more paperwork and exploring alternate options. Patient Volume Hospitals are among the busiest places on earth. Unfortunately, this puts excessive pressure on the staff to work around the clock. The high patient volume directly translates to tons of paperwork, reports, and bills. Using RCM software and data analytics helps handle this high volume. Fraud Detection The hospital staff also has to deal with fraudulent transactions and wrong insurance claims. Manually investigating each claim is exhausting. What if they can detect and predict such activities proactively? RCM analysis can be used for fraud detection to identify potential frauds in the early stages. In-house vs. Outsourced RCM Analytics in Healthcare: Which One to Choose RCM analytics can help healthcare businesses overcome various challenges they face in managing patient data and claims. But should they develop an in-house RCM analytics model or outsource RCM analytics to a third-party service provider? Which method is more effective? In-House RCM Let’s first check out what in-house RCM analytics in healthcare and medical billing actually are. In-house RCM is also called medical billing. The entire setup is managed by the hospital staff with little or no input from service providers. The service provider might build the RCM analytics model and hand over the responsibility to the hospital staff. This gives the business more control over the process but also increases workload. Advantages of In-house RCM Disadvantages of In-house RCM Outsourced RCM Analytics Outsourced RCM analytics are offered by third-party companies that handle all the responsibilities of setting up the analytical model, creating integrations between different systems within the establishment, and managing the central repository with patients’ details. What is outsourced RCM analysis in healthcare and medical billing? It is an interconnected approach to setting up a comprehensive and robust management system on a cloud platform to streamline and automate financial management in the healthcare center. A single interface or platform like the Power BI dashboard can be used by various departments like the front desk, billing, clinical, etc., to access patient data and update the records in real-time. It is a collaborative model aimed at boosting overall efficiency, performance, and revenue for the business. Advantages of Outsourced RCM Analytics Disadvantages of Outsourced RCM Analytics What are the 12 Steps of RCM? Data analytics companies offer nearshore and offshore RCM analytics services in the healthcare industry. They set up RCM analytics to streamline the twelve steps of revenue cycle management, manage patient data, track claims, and increase ROI. They start by identifying the KPIs to measure and improve the establishment’s financial health. What is a KPI in RCM? KPI stands for Key Performance Indicator, a metric used to measure if the RCM cycle is aligned with the hospital’s vision and objectives and is delivering the required results. The twelve steps of revenue cycle management in medical billing are as follows: Fortunately, hospitals can manage all these steps by investing in the latest revenue cycle management technology and partnering with analytics service providers to maintain the system. This reduces the pressure on hospital employees and enhances patient experience. It also maximizes efficiency and increases reimbursements by limiting denials. Conclusion Depending on the business’s mission, vision, and objectives, RCM

Yashica Chopra
January 10, 2025
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Singapore’s Leading IT Staff Augmentation Companies: Top 12 Pioneers

IT staff augmentation is an outsourcing model for organizations to quickly augment their in-house teams with external talent. Here, we’ll discuss the top twelve IT staff augmentation companies offering services expert teams to businesses in Singapore. In today’s competitive world, every business needs to strengthen its human resources to achieve the desired goals. Technology is helpful only when the right talent works with it, increasing efficiency and performance. However, recruiting is expensive and time-consuming. Moreover, there’s no guarantee that the employees will stay with the enterprise for long. In such instances, it makes sense to invest in staff augmentation services. Staff augmentation is a part of the outsourcing business model where expert professionals are hired to extend an existing team or build a new team to work on business projects. The teams can be of any size and work remotely or in person. They can stay with the organization for days, weeks, months, or years, depending on the project requirements. The Singapore Business Federation (SBF) released the National Business Survey (NBS) 2024 – Annual Business Sentiments Edition detailing the country’s economy and opportunities. Businesses expect improved economies in 2025, though they seem to worry about the increase in manpower costs. This can be strategically tackled by partnering with IT staff augmentation companies to hire talent temporarily. Many IT staff augmentation companies from Singapore and around the world offer tailored services to help businesses bridge the gap between required and existing human resources in their establishments. According to Verified Market Research, the global IT staff augmentation market size was $299.3 billion in 2023 and is expected to reach $857.2 billion by 2031 at a CAGR (compound annual growth rate) of 13.2%. In this blog, we’ll read about the top IT staff augmentation service providers that work with Singaporean businesses. 12 Top IT Staff Augmentation Companies in Singapore DataToBiz DataToBiz is a data science, AI, and staff augmentation services company with clients from over twenty countries around the globe. It works with startups as well as large enterprises and Fortune 500 firms to provide customized end-to-end services for varied requirements. The company provides certified IT professionals in just 48 hours and can quickly build a team as per the client’s specifications. It has a transparent pricing model and offers flexible plans to choose from – contract staffing, dedicated teams, full-time equivalent, PEO, contingent staffing, project-based hiring, and specialized skill acquisition. Businesses can also decide between hourly wages, monthly salaries, and other payment options. DataToBiz is a certified partner of Microsoft (Gold), AWS, and Google. It also has ISO certification and prioritizes data security and data privacy to ensure 100% client satisfaction. Slash Company Slash Company is a venture studio, tech partner, tech enabler, and one of the well-known staff aug companies in Singapore. It helps venture capitalists and startups enhance their tech infrastructure and accelerate growth. The company emphasizes innovation and how their services impact the businesses. Through its IT outsourcing and staff augmentation services, organizations can leverage a wide talent pool to improve operational efficiency and quickly fill important roles without long-term hiring commitments. Slash Company offers experienced professionals across various competencies, including technical and managerial roles, to handle projects successfully. Additionally, the company also provides augmented experts for leadership positions like CTO (Chief Technical Officer) to empower clients in using advanced technologies effectively. The external teams can work remotely and in person. Technology Bench Technology Bench is an IT service provider offering cutting-edge one-stop solutions to businesses through a dynamic and customer-centric approach. Its resource augmentation services are customized to help clients fulfill their staffing and technology needs in a short time. The company offers a range of IT specialists and developers for hire and provides ongoing support services to ensure the project is successful. From shortlisting the candidates to onboarding and initial training, everything is taken care of by the company. Technology Bench excels in handling industry-specific challenges to ensure sustainable business growth through the adoption and implementation of the latest useful technologies. Scalability and robust security measures are included as a part of the service to ensure clients’ projects are successful. Xcellink Group Xcellink Group is a trusted vendor partner to high-growth global businesses and local enterprises in Singapore. Its range of services, including resource augmentation services, data center operations, and on-field support help organizations strengthen their business processes and gain a competitive edge. The company also provides offshore staff augmentation to clients from different countries in Asia. Businesses can easily hire ICT professionals on a contract basis to take over tasks that need to be performed by experts. Xcellink Group also handles HR responsibilities to free time and resources for clients when managing augmented teams. The company is capable of dealing with complex project requirements and delivering the promised outcome. Be it a single-person team or a large one with diverse expertise, the company does it all. SP Sysnet – ICT Solution Provider SP Sysnet is an end-to-end infrastructure service provider offering varied solutions for businesses to enhance their processes and achieve goals in competitive markets. It displays the right combination of skills and attitude to help clients become successful in their industries. SP Sysnet helps drive revenue and profit by providing scalable external teams and temporary experts to work on clients’ requirements for cost-effective prices. As one of the IT staff augmentation companies in Singapore, the company assists businesses in adding the necessary talent at each level to build a reliable IT infrastructure with robust networks, dependable hardware, advanced databases, and much more. It also provides long-term support for ongoing tasks, allowing businesses to use augmented teams for extended durations. Madison Technologies Madison Technologies is an engineering team building digital products at scale and offering enhanced customer experiences. With a focus on research and planning, the company helps businesses develop innovative digital products that align with their respective industry standards. It offers dedicated teams through IT staff augmentation services to assist organizations that lack the required human resources and technology to achieve their objectives. The

Yashica Chopra
January 01, 2025
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Data Engineering Consulting in UAE – 15 Industry Experts to Know

Data is vital in today’s world and has to be effectively managed to achieve business goals. Here, we’ll discuss the data engineering consulting in UAE, top industry players and the importance of investing in them to revamp the business processes. Digital transformation has brought a vital change in how businesses look at data and manage their processes. It helps enterprises shift to a digital-first approach to make data-driven decisions in real time and grab market opportunities before competitors. Data engineering solutions are integral to digital transformation and a key element of the entire process. Data engineering is designing, building, implementing, and managing systems at scale to collect, store, analyze, and share data through a secure, automated, and cloud network. According to Market Data Forecast, the global big data and data engineering market is expected to be $75.55 billion in 2024 and projected to reach $276.7 billion by 2032 at a CAGR (compound annual growth rate) of 17.6%. There has been a definite increase in the adoption of data analytics and data engineering services in the UAE and other Middle Eastern countries. A report by Imarc shows that the Middle East data analytics market is projected to grow at a CAGR of 25.21% between 2024 and 2032. In this blog, we’ll read about the top fifteen data engineering consulting companies in Dubai and the extensive services they offer to business organizations from varied industries. Top Industry Experts in Data Engineering Consulting in UAE DataToBiz DataToBiz is a leading data engineering consulting company in UAE, offering tailored and end-to-end services to startups, SMBs, MSMEs, and large enterprises. As an award-winning and ISO-certified company, it offers data warehousing as a service (DWaaS), data architecture, data pipeline, and workflow automation services for clients to streamline their internal operations, reduce the consumption of resources, and understand customer preferences. The company is a certified partner of Microsoft (Gold), Google, and AWS. It has the required expertise and domain experience to set up scalable, flexible, and agile cloud-based IT infrastructure. DataToBiz offers industry-specific solutions through consulting, managed, remote, and staff augmentation services. Businesses can hire dedicated teams to work on-premises and remotely to experience the benefits of data engineering. Usetech Usetech calls itself a blockchain laboratory offering big tech consulting services to clients in Dubai and the Middle East. The company uses cloud computing and advanced technologies to provide data engineering, data analysis, and data visualization services for businesses from varied sectors. It has an experienced team of professionals to design and build data pipelines and set up the necessary connections to create seamless data flow within the enterprise. The company also migrates existing systems from on-premises to cloud servers. When implementing the changes, Usetech considers customer behavior and data security threats. Helping businesses use customer data to understand what the target audience wants correctly gives them a definite edge in competitive markets. Techcarrot Techcarrot is a global IT service provider offering a diverse spectrum of services, digital innovations, etc. The company operates in the UAE and works with clients from diverse sectors. It has an experienced data engineering team that collaborates with organizations and helps them find simple yet unique solutions to manage data and processes effectively. The company builds robust and scalable big data architectures as per the clients’ requirements, be it on-premises or cloud servers. Techcarrot helps businesses overcome data challenges and design systems for the future. It empowers businesses to make data-driven decisions based on reliable and meaningful insights and gain a competitive edge. Anderson Lab Anderson Lab is an innovative software development company offering data engineering consulting solutions through a team of skilled professionals and efficient processes. It partners with Microsoft, Oracle, AWS, ISTQB, and other tech giants to use advanced technologies to build effective data pipelines and architecture for clients. The company believes in making a global and local impact by closely collaborating with different organizations. Anderson Lab also emphasizes sustainability and knowledge sharing. It starts by conducting an audit to understand the current business position and then provides consulting services to help them overcome various challenges. The company increases the performance and scalability of the data systems in an enterprise. It helps reduce the time to market and expenses. Intellias Intellias is a global technology partner with a client base in the UAE and other countries. The company follows a people-centric approach to convert potential client ideas into tangible products, services, and systems. It can work with any complexity and scale, making things easier for startups as well as multinational organizations. The company’s data engineering services aim to unlock the full potential of business data and turn it into a valuable asset with high ROI. Intellias offers consulting and end-to-end services for strategizing, designing, building, implementing, and upgrading data engineering models for clients. It improves the accuracy of insights to eliminate risk and creates simple procedures that can be easily adopted across the enterprise. Sysvine Technologies Sysvine Technologies is a software product engineering and data engineering consulting company with a global client base. The company has a seasoned team that provides expert services for big data, data engineering, data analytics, and more through cloud, AI, and ML technologies. It focuses on quality, performance, and standardizing the processes to increase business efficiency and ROI. The company offers iPaaS (Integrated Platform as a Service) solutions for managing complex IT infrastructure and multiple third-party integrations seamlessly. This reduces the risk of error and downtime and provides real-time access to data and insights. Sysvine Technologies also offers enterprise data management services and builds scalable data architecture models that align with clients’ specifications. VentureDive VentureDive is a technology solutions company that laser-focuses on combining technology with human ingenuity. This data warehousing company provides custom data engineering services to deliver excellence by bringing data, people, and processes together. It defines an enterprise’s data landscape and builds scalable systems for long-term use. Businesses can achieve successful data-driven transformation and derive maximum value from their data assets. VentureDive takes care of strategy, design, data landscaping, data warehousing, data

Yashica Chopra
December 27, 2024
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A Modern Approach to Scalable Data Management Pipeline

A streamlined and automated data pipeline is the core of a well-built IT infrastructure and results in proactive decision-making. Here, we’ll discuss the detailed guide into a modern approach to data management pipeline and how to build a robust data system in your enterprise. Data is the core of every business in today’s world. You can no longer ignore the importance of data and its role in running an establishment. Whether a startup or a large enterprise with a presence in multiple countries, data holds the key to insights that help make better decisions. It doesn’t matter which industry you belong to. Business and third-party data are necessary to make informed choices in all verticals. As per Statista, the total amount of data created and consumed globally was 149 zettabytes in 2024 and is expected to be over 394 zettabytes by 2028. But how will you manage large amounts of data in your enterprise? How will you store it when more data is added every day? How will you clean and organize the datasets? How will you convert raw data into actionable insights? That’s where data management and data engineering help. Data management is the process of collecting, ingesting, preparing, organizing, storing, maintaining, and securing vast datasets throughout the organization. It is a continuous and multi-stage process that requires domain expertise and knowledge. Luckily, you can hire a data engineering company to provide end-to-end services for data management. In this blog, we’ll learn more about data management’s process, tools, and pipeline and how it can benefit your business in the long run. How the Data Management Process Works? According to a report by IOT Analytics, the global data management and analytics market is predicted to grow at a CAGR (compound annual growth rate) of 16% to reach $513.3 billion by 2030. The modern data management workflow relies on various tools and applications. For example, you need a repository to store the data, APIs to connect data sources to the database, analytical tools to process the data, etc. Instead of leaving the data in individual departmental silos, the experts will collect the data and store it in a central repository. This can be a data warehouse or a data lake. Typically, these can be on-premises in physical units or cloud servers in remote locations (data centers). The necessary connections are set up for data to be sent from one source to another. These are called data pipelines. The data management process broadly includes seven stages, which are listed below. Data architecture is the IT framework designed to plan the entire data flow and management strategy in your business. The data engineer will create a blueprint and list the necessary tools, technologies, etc., to initiate the process. It provides the standards for how data is managed throughout the lifecycle to provide high-quality and reliable outcomes. Data modeling is the visual representation of how large datasets will be managed in your enterprise. It defines the relationships and connections between different applications and charts the flowchart of data movement from one department to another or within the departments. Data pipelines are workflows that are automated using advanced tools to ensure data seamlessly moves from one location to another. The pipelines include the ETL (extract, transform, load) and ELT (extract, load, transform) processes. These can be on-premises or on cloud servers. For example, you can completely build and automate the data management system on Microsoft Azure or AWS cloud. Data cataloging is the process of creating a highly detailed and comprehensive inventory of the various data assets owned by an enterprise. This includes metadata like definitions, access controls, usage, tags, lineage, etc. Data catalogs are used to optimize data use in a business and define how the datasets can be utilized for various types of analytics. Data governance is a set of frameworks and guidelines established to ensure the data used in your business is secure and adheres to global compliance regulations. This documentation has to be followed by everyone to prevent unlawful usage of data. The policies ensure proper procedures for data monitoring, data stewardship, etc. Data integration is where different software applications and systems are connected to collect data from several sources. Businesses need accurate and complete data to derive meaningful analytical reports and insights. This is possible by integrating different third-party systems into the central repository. Data integration also helps in building better collaborations between teams, departments, and businesses. Data security is a vital part of the data management pipeline and a crucial element in data engineering services. It prevents unauthorized users and outsiders from accessing confidential data in your systems. It reduces the risk of cyberattacks through well-defined policies. Data engineers recommend installing multiple security layers to prevent breaches. Data masking, encryption, redaction, etc., are some procedures to ensure data security. A Guide to Scalable Data Management Pipeline The data management pipeline is a series of steps and processes required to prepare data for analysis and share data visualizations with end users (employees) through the dashboards. It automates the data flow, increases system flexibility and scalability, improves data quality, and helps in delivering real-time insights. Steps to Building a Data Management Pipeline Define Objectives and Requirements The first step in building a data management pipeline is to know what you want to achieve. Focus on the short-term and long-term goals to build a solution that can be scaled as necessary. Discuss the details with department heads and mid-level employees to consider their input. Make a list of challenges you want to resolve by streamlining the data systems. Once done, consult a service provider to understand the requirements and timeline of the project. Aspects like metrics, budget, service provider’s expertise, etc., should be considered. Identify and List the Data Sources The next step is to identify the sources to collect the required data. These will be internal and external. Determine what type of data you want (unstructured, semi-structured, or structured), how frequently new data should be uploaded to the repository, how

Manpreet Kaur
December 24, 2024
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Inside Look at MENA’s Top 11 Data Analytics Companies (Exclusive List)

Many organizations in the Middle East and North Africa (MENA) region don’t fully use their data due to limited data analytics infrastructure. Data analytics companies are stepping in to help, offering services that allow businesses to understand their data and use it effectively. They help organizations gain valuable insights into their operations, customers, and market trends in the MENA region. “If we have data, let’s look at data. If all we have are opinions, let’s go with mine.” — Jim Barksdale. Having said that, data analytics for business has become imperative for organizations across different industries. As companies collect vast amounts of data from varied sources such as transactions, customer interactions, and market trends, it is important to analyze and interpret this information to make strategic decisions. According to IMARC the data analytics market in Middle East data is projected to grow at a CAGR of 25.21% during 2024-2032. Interestingly, the data analytics market in the MENA region is expected to grow at a CAGR of 18.2% and is projected to reach US $15,714.4 by 2030. In this blog, we’ve compiled a list of top data analytics companies in the Middle East specializing in data engineering services to help organizations transform data analytics. Why are data analytics companies important for businesses? Data analytics is important for organizations across various sectors and helps them to take strategic advantage of their data by understanding market trends and customer needs. This allows them to stay ahead of competitors. Here’s why data analytics is important: Organizations can partner with data analytics companies to identify potential risks and take measures to mitigate those risks. These data analytics companies provide organizations with data-driven insights, enabling them to make informed decisions based on factual information rather than assumptions. By identifying inefficiencies, data analytics helps organizations to optimize their processes, reduce costs, and allocate resources effectively. Analyzing customer data makes it easy to understand preferences and behaviors so that businesses can offer personalized services and enhance customer satisfaction. MENA’s Top 11 Data Analytics Companies (Exclusive List) DataToBiz DataToBiz is a data analytics company offering a rich array of data engineering services focusing on Microsoft Azure, AWS, and Google Cloud. Their team of professionals helps organizations manage, process, and analyze large volumes of data effectively. The company also offers strategic consulting to help organizations define and architect data strategies that align with their goals. Moro Hub Moro Hub, a subsidiary of Digital DEWA (Dubai Electricity and Water Authority), is a UAE-based digital data company that offers digital transformation and operational services. It offers various data analytics services designed to help organizations use their data for informed decision-making and strategic planning. Further, it helps you to make the most out of your data assets by offering data engineering consulting, integrating various data sources seamlessly, and processing them to derive actionable insights. LRB Infotech LRB Infotech specializes in Big Data Analytics, helping businesses to transform raw data into actionable insights. By offering advanced solutions for data management, integration, and analysis, the company allows organizations to optimize operations, predict trends, and make informed decisions. The team has extensive expertise in predictive, descriptive, and prescriptive analytics, helping businesses to find patterns and identify upcoming challenges, and growth opportunities. Data Semantics Data Semantics is one of the best data analytics companies that specializes in using advanced technologies to streamline business operations. It helps organizations by delivering AI-driven solutions to extract meaningful insights and increase efficiency. The company provides a comprehensive suite of data analytics solutions that come with reporting and visualization capabilities, offering real-time insights for decision-making. Clariba Consulting With a presence of more than 24 years, Clariba Consulting is a prominent provider in the list of data analytics for businesses and data engineering companies. It aims to deliver advanced solutions that help organizations to harness their data effectively. The company offers tailored analytics and business intelligence services that help clients make informed decisions. One of its flagship products includes Delfos by SEIDOR, a virtual assistant that allows interaction with data, documents, systems, and processes through conversational AI. XenonStack XenonStack is a leading data analytics company with a focus on Big Data and real-time analytics services. The company provides comprehensive consulting services that help organizations to use their data through robust analytical capabilities. Some of their solutions include automated data ingestion, real-time insights, and business intelligence powered by tools like Power BI. These solutions enable organizations to streamline operations and enhance decision-making processes through insights obtained from large datasets. Beinex Beinex is a data analytics company that offers a rich range of services such as business intelligence, advanced analytics, risk management, and competitive intelligence. The company is known for its commitment to using innovative technologies to drive business success. Its advanced analytics and data engineering services enable organizations to analyze data, find patterns and trends, identify opportunities, predict outcomes, and mitigate risks. Mobcoder Launched in 2014, Mobcoder is a technology company that offers a wide range of services, including data analytics for businesses. With over 300 applications, the company is a reliable partner for organizations looking to use technology for growth and efficiency. Its data analytics services help you gain insights and make informed decisions by transforming raw data into meaningful intelligence. Some of its analytical offerings include Big Data, data warehousing, dynamic reporting, and NLP. Accenture Accenture is a global leader in data analytics and offers comprehensive solutions that empower organizations to use their data sets effectively. With a focus on digital transformation, it integrates advanced analytics into its offering, thereby helping businesses across various industries. The company also offers data strategy consulting, data management, and architecture strategies. Some of its main services include modernizing legacy systems and developing cloud-based data architectures. Cognizant Cognizant is a prominent player in the field of data analytics and offers solutions for data ingestion, storage, advanced analytics, and AI-driven insights. Its services help organizations with advanced DataOps, automation, and AI-driven insights. The company also offers next-generation data ecosystems that democratize access to data, thereby allowing businesses to

Yashica Chopra
December 19, 2024
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15+ Next Gen ML Engineering Companies – The 2025 Watchlist

Be it Azure data engineering or AWS IaaS solutions, managing the ML model lifecycle is crucial for businesses to derive actionable insights. Here, we’ll discuss the top fifteen ML engineering companies, businesses can partner with in 2025 to optimize their data-driven models. Machine learning is part of artificial intelligence and involves algorithms that support an application or a model. Businesses that invest in AI also use machine learning, data engineering, cloud solutions, and other relevant technologies to transform their processes digitally and vertically. The global ML engineering market is expected to be $79.29 billion in 2024 and reach $503.40 billion by 2030 at a CAGR (compound annual growth rate) of 36.08%. According to Fortune Business Insights, the global MLOps market size was $1,064.4 million in 2023 and is expected to reach $13,321.8 million by 2030 at a CAGR of 43.5%. According to the Business Research Company, North America is the largest region driving growth in the MLOps market. Straits Research says that North America is the dominant region in MLOps adoption with a 45.2% market share. More statistics show that 57% of businesses use machine learning to enhance customer experience, while 49% use it in sales and marketing. Additionally, 48% of businesses worldwide use ML models and technologies in some form. Like other advanced technologies, machine learning requires expert talent and skills. Enterprises should hire ML engineers, data scientists, data analysts, etc., to build, develop, and maintain machine learning models in their business. Since starting from scratch is cost-intensive, organizations can partner with ML engineering companies to gain access to the required talent and technologies. Working with a certified service provider reduces the risk of losses and increases the success rate. In this blog, we’ll learn more about MLOps and the top fifteen companies offering this service in 2025. What is ML Engineering? Machine Learning (ML) Engineering is short for machine learning operations, a practice set that simplifies and automates ML workflows. It is the central function of machine learning engineering and deals with the development, deployment, monitoring, and maintenance of various ML algorithms and models that support business operations. MLOps is not an independent activity but a collaborative practice that includes data science, DevOps, data engineering, data analytics, and more. It is useful in many ways. A few examples of machine learning engineering include demand forecasting, automation, product recommendations, sentiment analysis, measuring customer lifetime value, etc. In North America (USA), ML engineering is an integral part of data engineering. During the last few years, there has been a 74% annual growth in demand for ML and AI-related roles. The demand will continue and grow by 40% between 2023 and 2027. The average pay of an MLOps engineer is $100K per year, making it a lucrative option for IT professionals. Meanwhile, organizations are actively partnering with experienced service providers to make the most of their data engineering and MLOps services. The BSFI industry has the highest share of MLOps (over 18%) for fraud detection, yield management, preventive maintenance, etc. Businesses will find it convenient and cost-effective to build, deploy, and maintain the MLOps frameworks on cloud platforms like Azure, AWS, and Google. This also empowers the organization during its digital transformation journey and reduces the pressure of maintaining the expensive IT infrastructure on-premises. The machine learning lifecycle is complex and includes many stages, starting from data ingestion (feeding data to the algorithm). This requires a team effort from experienced professionals and strict regulations to ensure the models work accurately and provide reliable results. Additionally, the ML models have to be continuously monitored to improve the process and enhance the outcome. Since data is the core of AI and ML models, organizations should hire companies that offer end-to-end data engineering services along with MLOps solutions. Next-Gen ML Engineering Companies To Watch Out For! DataToBiz DataToBiz is among the best ML engineering companies offering end-to-end and tailored AI and ML solutions for startups, SMBs, and large enterprises from different parts of the world. The company is a certified partner of Microsoft (Gold), AWS, and Google. It provides customized cloud development and transformation services, along with artificial intelligence consulting, data warehousing, data analytics, etc. With guaranteed NDA and IP protection, the company ensures the client’s confidential data remains safe. Businesses can achieve flexibility, scalability, and agility in their workflows by partnering with the company. DataToBiz relies on advanced and effective MLOps technologies to streamline, automate, manage, and continuously improve the machine learning models in an enterprise. Businesses can make accurate and proactive data-driven decisions in real-time and achieve success. Fractal Analytics Fractal Analytics is on the leading ML engineering companies list of USA-based service providers. It helps clients bridge the gap between machine learning development and enterprise production development by optimizing internal processes. The company manages everything from data collection to model training and deployment, long-term maintenance, and regular upgrades. By automating the deployment of ML models, the professionals create a streamlined solution that sustains the data-driven models in an enterprise. Since continuous training and continuous monitoring are a part of MLOps, businesses can be assured of developing a reliable machine learning model to analyze large amounts of historical and real-time data. Fractal Analytics offers MLOps services in three ways – building MVP, staff augmentation, and full project. Tiger Analytics Tiger Analytics is an AI and analytics service provider that helps businesses solve various challenges hindering their growth. The company uses the best MLOps tools to make sure the AI and ML models deliver accurate and reliable results throughout their lifecycle. Be it faster development cycles, seamless fine-tuning, continuous improvement, or robust maintenance, the company takes care of everything. It follows the engineering best practices to build, deploy, test, maintain, and monitor the machine learning models for different departments and verticals in an enterprise. Tiger Analytics offers MLOps as a strategy and a service alongside DevOps as a service through public and private cloud platforms. It builds powerful cloud-native apps for businesses to make real-time decisions. Genpact Genpact is a software and

Yashica Chopra
December 18, 2024
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Your 10 Step Guide to Data Domination in 2025

Data domination allows businesses to make informed and data-driven decisions using real-time actionable insights. Here, we’ll discuss the guide to data domination through tailored data engineering services for your business. Data domination is the process of streamlining and effectively managing datasets to benefit from the data-driven model and make proactive decisions. It is a blueprint to implement data engineering and management solutions in your enterprise. So does it mean data engineering necessary is in 2025? Absolutely! Statistics show that the global big data and data engineering market will be $75.55 billion in 2024 and expected to reach $169.9 billion by 2029 at a CAGR (compound annual growth rate) of 17.6%. It is evident data engineering services are not only necessary for 2025 but will continue to play a prominent role even afterward. Of course, data domination is easier said than done. You should consider many factors like data collection methods, data ingestion, safe and secure data storage, long-term maintenance, troubleshooting, etc. Not addressing these concerns can lead to failed data management systems. That would be counterproductive, isn’t it? Luckily, you can overcome these challenges and more by partnering with a reliable data engineering company. Hire experts from the field to mitigate risks and increase your success rate. Let’s check out the detailed guide to data domination in 2025. Before that, we’ll find out how to overcome the challenges in data engineering. Challenges for Data Domination and How to Overcome Them As per Gartner, poor data quality leads to a loss of $15 million annually for businesses around the world. Avoiding this and many other pitfalls is easy when you make informed decisions. By overcoming these challenges, you will be several steps closer to data domination and gain a competitive edge. Data Ingestion Data ingestion refers to feeding data from multiple sources into your systems. It is one of the initial steps of data engineering solutions. The data ingested is then cleaned, processed, and analyzed to derive insights. A few challenges you might face are as follows: These issues can be sorted by in-depth planning. Instead of immediately connecting the data sources to your systems, take time to identify the right sources and set up data validation and cleaning processes (ETL and ELT). Automate the process to save time and reduce the risk of human error. Determine your budget and long-term goals when deciding the data ingestion method. Migrate to cloud platforms for better infrastructure support. Data Integration Data integration depends on how well the various software solutions, applications, and tools used in your enterprise are connected to each other. Naturally, data will be in different formats and styles depending on the source. A few more challenges are listed below: For seamless data integration, you should first create a data flow blueprint. Then, identify software solutions that are not compatible with others (legacy systems) and modernize or replace them. Since you have to integrate different data types (structured, unstructured, and semi-structured), you should invest in data transformation tools. Azure data engineering services cover all these and more! Data Storage The biggest concern about data storage is scalability. With so much data being collected in real time, where will you store it? Moreover, how much can your data storage centers handle the load? What to do with old data? How hard will it be to retrieve data from the storage centers? Here are more challenges to consider: Choosing the wrong data storage model can adversely affect the entire data engineering pipeline. Migrating to cloud servers is an effective way to overcome these roadblocks. For example, Azure, AWS, or Google Cloud platforms offer flexible, scalable, and agile data warehousing solutions. You can set up a customized central data warehouse that can be upgraded whenever necessary. A data warehouse is capable of handling large datasets and can quickly respond to queries. Data Processing Traditional data processing tools cannot handle diverse data. They also cannot process large datasets quickly. Processing data from silos can lead to data duplication and reduce the accuracy of the results. There are more data processing concerns, such as: Modern problems require modern solutions. Instead of struggling with traditional tools, switch over to advanced technologies and AI-powered data processing tools. Similarly, data silos have to be replaced with a central data repository like a data warehouse or a data lake. Partnering with AWS data engineering companies will help you identify the right tools and technologies to process data in real time and share the insights with employees through customized data visualization dashboards. Data Security and Privacy Data brings more challenges with it. After all, you are using data that includes confidential information about your customers, target audiences, competitors, and others. How to ensure this data is safe from hackers? How to avoid lawsuits from others for using their data for your insights? Common data security concerns are: Data security should be included as a part of data warehousing services. Data encryption, data backup, disaster recovery management, authorized access to stakeholders, security surveillance, security patch management, and employee training (to create awareness about cyber threats), etc., are some ways to overcome these challenges. The service provider will also create a detailed data governance guide to provide the framework for regulatory compliance. 10-Step Guide to Data Domination in 2025 Step 1: Define Business Goals Always start at the beginning. Lay the foundations clearly and carefully. What do you want to achieve through data domination? How will your business improve through data engineering? What are your long-term objectives? Be detailed in defining the business goals so that your stakeholders and service providers understand the requirements. Step 2: Hiring a Data Engineering Company Data domination is not an easy task. It’s a multi-step and continuous process that requires expertise in different domains. While you can build a team from scratch by hiring data engineers, it is cost-effective and quick to hire data engineering or a data warehousing company. Make sure it offers end-to-end services and works remotely. Step 3: Create a Data Domination Strategy

Yashica Chopra
December 15, 2024
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AI as a Service – A Bold Move in 2025?

Artificial intelligence as a service (AIaaS) is a cloud-based solution for enterprises to invest in advanced technology. Here, we’ll discuss AIaaS, its role in today’s market, and how businesses achieve their goals by partnering with AI service providers. The adoption rate of artificial intelligence has increased multifold over the years. Many businesses, be they startups or established enterprises, are investing in AI in varied ways to gain a competitive edge and survive volatile market conditions. According to Grandview Research, the AI market is likely to experience an annual growth rate of 37.7% between 2023 and 2030. A report by Markets & Markets shows that the global AI market is predicted to reach $1.3 trillion by 2030. Fortunately for businesses, nonprofits, and government agencies, any organization can adopt AI technology on any scale. It can be a tiny part of your business process or be 100% integrated into all processes across the departments and verticals. Moreover, artificial intelligence services are diverse and customizable. Naturally, this led to a relatively new cloud-based AI offering called AI as a service (AIaaS). This is more convenient, budget-friendly, and effective compared to large-scale AI adoption and implementation. But what exactly is AIaaS? What does an AI services company do to offer artificial intelligence as a cloud service? Will it be a worthy choice for businesses in 2025? Let’s find out! What is the AI Model as a Service? AI as a service (AIaaS) is a new business model where service providers offer artificial intelligence-based solutions through a cloud platform. Instead of setting up the AI tools/ apps on-premises, the software is hosted on a remote cloud server and accessed by users whenever necessary. All technologies and tools under the umbrella term AI are available on the cloud. Be it machine learning algorithms, natural language processing (NLP) models, large language models (LLMs), generative AI apps, computer vision, advanced analytical tools, etc., can be accessed remotely to get near real-time and real-time results. In the AI as a service business model, you subscribe to use the required tools and software provided by the vendors. You pay only for what to use and not for all the other services offered. Additionally, the pay-as-you-go model allows startups and emerging businesses to save money on unwanted expenses. You can upgrade or downgrade the subscription plan as necessary. Furthermore, there’s no need to invest heavily in building the IT infrastructure in the office. Employees can use their personal devices and work from any location as long as they have been authorized to access the tools. What is the Purpose of AI as a service? As per Global Market Insights, the AI as a service market size is expected to grow at a CAGR (compound annual growth rate) of 28% between 2023 and 2032 and reach $75 billion by 2032. This growth rate can be attributed to the ease of using artificial intelligence as a cloud service. The main purpose of AIaaS is to eliminate the need for unwanted hardware and bring greater flexibility to the business’s IT infrastructure. AI as a service is diverse and can be classified into the following types. Whether you want to implement only one of the above or a combination (and all of them), the AI product development company will create a price plan accordingly and determine the subscription charges. That way, you pay for what you use while ensuring quality, scalability, agility, and personalization are not compromised. Of course, there can be a few concerns like data security, lock-in agreements, and transparency about the core AI systems used. However, these issues are a problem only if you choose a service provider at random. Many reliable companies that offer AI as a service address these concerns proactively. For example, DataToBiz is an ISO-certified AIaaS company that complies with global data regulations and has a transparent pricing model. The developers use existing cloud technologies or build new models based on clients’ requirements. With the right partner, you can vastly benefit from switching to the AIaaS business model. Why You Should Invest in AI as a service? What makes AI as a service a better alternative to implementing artificial intelligence in your business? Check out below. With AIaaS, an organization can quickly build, develop, and release products into the market. The production cycle can be shortened without affecting quality and performance. AI product development in today’s world results in low-code or no-code applications that can be built and customized in a fraction of the time usually required to develop a model from scratch. The drag-and-drop interfaces accelerate time to market and allow you to quickly launch new products before competitors. AI as a service is a long-term solution or an agreement with the service provider. As long as you pay for the subscription, you will get continuous improvements and upgrades offered by the company. In most enterprise price plans, you don’t have to pay extra for troubleshooting, upgrading, or maintenance services. The service provider offers these as a part of the package. Over the years, you gain more from the service and see positive growth in ROI. Advanced technology is not cheap, and not every business has the capacity to buy new tools and software as soon as they are released. What will you do with the existing apps? How many can you buy only to use for a limited period? However, with AI as a service, there’s no need to make huge purchases. You can use the latest tools without buying them outright. That makes it feasible for startups and small businesses to use technology just like large enterprises do. The stakes are lower as you can switch from one service provider to another or use a different platform if the current one doesn’t meet your expectations. As mentioned earlier, AI as a service offers more flexibility in choosing what features, tools, frameworks, and solutions to implement in a business. There’s no need to complicate the systems by trying to use every available option for its own sake.

Yashica Chopra
December 11, 2024
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Why do Growing Enterprises Need a Digital Transformation Consultant?

Digital transformation is a never-ending process of using advanced technology and data-driven models to make effective business decisions. Here, we’ll explore the need for hiring a digital transformation consultant to boost an enterprise’s growth and ensure consistent results. Whether you own a startup or belong to a multinational company, the organization uses a range of applications, systems, and tools to manage daily activities. In today’s world, businesses need to rely on technology to quickly achieve their goals. You cannot compete with digitally strong firms without investing in the latest technology. That’s where digital transformation helps. According to a survey by West Monroe, 61% of C-suite executives recognize digital transformation as a priority. A report by Valtech shows that 94% of large enterprises in the US and the UK have a digital transformation strategy in place to revamp their systems and processes. The same report says 58% of businesses aim to increase their spending on digital transformation compared to previous years. In such instances, it’s vital to understand what digital transformation is and how a digital transformation consultant can help you with the process from end to end. In this blog, we’ll focus on the role of a digital transformation consultant in a growing enterprise. What is Digital Transformation? Digital transformation is a continuous process and a business strategy to integrate various digital technologies into the business at different levels and verticals. It helps in evaluating the existing systems and modernizing them to create a digital-first approach to running the business. From procurement to production, operation management to customer service, and finance to marketing, every aspect of the business is streamlined using relevant digital technology. Modern-day concepts like personalization, agility, scalability, flexibility, etc., can be achieved by digitally transforming business processes. It is a comprehensive way forward to be proactive in competitive markets and increase brand visibility. Digital transformation, when rightly done, increases revenue for the organization and accelerates growth. Technologies like cloud computing, artificial intelligence, machine learning, advanced analytics, data science, big data, IoT (Internet of Things), edge computing, data visualization, business intelligence, etc., are a part of digital transformation. As an employee or a C-suite executive, you may ask – what is my role in digital transformation? Well, your role is varied and depends on how you want to digitally transform the enterprise. You need to work with an experienced digital transformation consultant to create the strategy, determine the budget, and initiate the process. What Does a Digital Transformation Consultant Do? According to Market Research Future, the digital transformation consulting market size was $205.87 billion in 2023 and is expected to reach $386.73 billion by 2032 at a CAGR (compound annual growth rate) of 7.40% between 2024 and 2032. With digital transformation explained in the previous section, let’s see what a digital transformation consultant does and how they can help your business. Digital transformation is different from digitization, which is a process of converting analog data into digital data. It has a wider scope and involves all parts of the business. A digital transformation consultant is a qualified and certified expert who guides business organizations in understanding, implementing, and managing the digital transformation journey. Consultants work as freelancers or can belong to a digital transformation services company. Their role is to help enterprises bridge the gap between technical knowledge and their long-term objectives, identify tools that align with the establishment’s needs, and create a holistic environment for employees to adopt the new technologies. However, this is a broader description of what a digital transformation consultant does. In reality, their work is much more complex and time-consuming. Their strategies are developed based on the requirements of each business and the unique challenges faced by them. From streamlining the processes in each department to automating repetitive tasks, setting up third-party integrations, and providing data-driven insights, the digital transformation consultant has to consider several aspects when assisting a business on its digital transformation journey. Why is Digital Transformation Important? Digital transformation consulting services are important in many ways in the modern-day scenario. From improving operational efficiency to enhancing customer experience, it helps growing enterprises harness the latest technologies to boost their business. It is not limited to a single industry and can be effective in any business. Despite being a tech-based long-term solution, its presence is useful in every sector and industry. The digital transformation strategy is prepared for the long term and empowers a business to continuously innovate and come up with better processes. Agile and DevOps practices are integrated with emerging technologies to make the applications more effective. Furthermore, it is helpful in future-proofing a business. The internal and external operations of an organization need to run in a smooth rhythm to provide the necessary products and services to customers (end-users). With digital transformation, you can optimize the operations using relevant tools, applications, and software. Automation is the process of using technology to perform the tasks previously handled by humans. This saves time, reduces the consumption of resources, and minimizes the risk of human error. It is a critical part of digital transformation and can increase the overall productivity of an enterprise. Customer satisfaction should be a priority for every business. The digital transformation approach is also designed with a focus on increasing customer satisfaction (attracting new customers and retaining existing ones). You can use customer analytics to understand their preferences and take steps to increase brand loyalty. Change is the only constant in today’s world. Enterprises cannot resist change if they want to survive market competition. Digital transformation empowers organizations to become more resilient in adverse conditions and be quick to adapt to new developments. Flexibility is one of the top benefits of digital transformation. AI and ML technologies, along with cloud solutions, can revamp the IT infrastructure in an enterprise to make the workflows more efficient and result-oriented. Digital transformation helps identify unwanted tasks and simplify the processes. This encourages resource optimization and makes it easier for employees to finish their tasks quickly. The digital strategy consultant’s