While not a new field, data transformation projects have experienced significant growth over the past 12 to 18 months. This surge is in response to evolving business needs influenced by the proliferation of data and technological advancements, including streaming analytics and edge computing. These initiatives aim to achieve hyper-personalization, enhance internal data accessibility, increase customer engagement, and extract valuable insights from unstructured datasets. In turn, these efforts drive growth and innovation within organizations.
Both demand- and supply-side trends are covered in Avasant’s Data Management and Advanced Analytics Services 2023 Market Insights™ and Data Management and Advanced Analytics Services 2023 RadarView™, respectively. These reports present a comprehensive study of data management and advanced analytics service providers and closely examine the market leaders, innovators, disruptors, and challengers.
We evaluated 36 service providers across three dimensions: practice maturity, partner ecosystem, and investments and innovation. Of the 36 providers, we recognized 19 that brought the most value to the market during the past 12 months.
The report recognizes service providers in four categories:
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- Leaders: Accenture, Capgemini, Cognizant, HCLTech, IBM, Infosys, TCS, Tech Mahindra, and Wipro
- Innovators: Genpact, LTIMindtree, and UST
- Disruptors: Birlasoft, Hexaware, ITC Infotech
- Challengers: Apexon, Coforge, SG Analytics, Zensar
Figure 1 below from the full report illustrates these categories:
“Generative AI is a game changer in data management and analytics, helping enterprises monetize data, create dynamic visualizations, and facilitate seamless processing,” said Anupam Govil, Avasant partner and digital practice lead. “It revolutionizes how we interact with and derive value from data, offering unrivaled innovation opportunities.”
The reports provide several findings, including the following:
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- In the past year, data management and advanced analytics projects have increased by 1.2 times. ESG data preparation and reporting, generative AI, data monetization, and event stream processing are expanding the horizons of data and analytics initiatives.
- About 76% of data and analytics projects concentrate on data engineering and security, with a strong emphasis on data modernization, migration, and transfer, followed by data operation pipeline and data lake creation and data governance enablement.
- After cloud and cybersecurity, enterprises place big data analytics as their third most critical priority, primarily to understand consumer behavior and improve decision-making. Notable big data analytics use cases gaining traction across industries encompass fraud, lending, and trading analytics in BFSI; customer and supply chain analytics in retail and CPG; and patient engagement, billing fraud, and claim pattern detection analytics in healthcare and life sciences.
- Customer service, finance, accounting, and IT departments are the hotspots of data and analytics initiatives. This strategic realignment stems from the understanding that data-driven insights are indispensable for critical tasks spanning budget forecasting, customer journey mapping, and IT infrastructure performance monitoring.
“Enterprises recognize that a robust data architecture is essential for leveraging emerging technologies,” said Chandrika Dutt, research leader with Avasant. “This has led to an emphasis on integrating modern data concepts such as data fabric and data mesh as fundamental architectural elements, enabling agility in their data-centric strategies.”
The Data Management and Advanced Analytics Services 2023 RadarView™ report features detailed RadarView profiles of 19 service providers, along with their solutions, offerings, and experience in assisting enterprises in their data management and advanced analytics journeys.
This Research Byte is a brief overview of the Data Management and Advanced Analytics Services 2023 Market Insights™ and Data Management and Advanced Analytics Services 2023 RadarView™ (click for pricing).
