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Why Data Management is Critical to Business Success
Why Data Management is Critical to Business Success

Entrepreneur

time4 days ago

  • Business
  • Entrepreneur

Why Data Management is Critical to Business Success

Data is the lifeblood of our interconnected world, and a crucial lever for driving exceptional customer experiences, says Rajiv Shesh Chief Revenue Officer, HCL Software Opinions expressed by Entrepreneur contributors are their own. You're reading Entrepreneur India, an international franchise of Entrepreneur Media. In an era defined by digital transfor mation, data has emerged as the most critical asset for organizations seeking to thrive in a hyper competitive landscape. The ability to effectively capture, manage, and leverage data is no longer a competitive advantage, it is a major business imperative. Navigating The Data Deluge Data is the lifeblood of our interconnected world, and a crucial lever for driving exceptional customer experiences. As data volumes explode, stakeholders face mounting risks and complexity in classifying, managing, and identify ing what truly matters. The solution lies in a unified environment that seamlessly integrates, processes, and manages data across diverse sys tems, enabling effective data lineage. Consider Real World Use Cases A leading insurer needed to transform its under writing platform for rapid online quotes while upholding risk stan dards. By implementing a sophisticated data management platform, they integrated multiple validation services and third-party sources, delivering personalized insurance pricing within 400 milliseconds. This also allowed them to triple their data team size without performance degradation and imple ment real-time analytics dashboards. Similarly, a mid-sized software firm, competing with giants, revamped its customer engage ment by solving critical data integration chal lenges. A cohesive data management platform unified customer data from myriad sources, empowering sales, and marketing with instant insights for personalized experiences from day one, deployable across multiple clouds. Factors To Look For Evaluating Data Evaluating data man agement tools requires focusing on critical capabilities such as scal ability and reliability. To handle large volumes of data for real-time deci sions, organizations need to pivot away from data silos and adopt a unified approach. Enterprises looking to adopt a data management platform must look for flexible, re liable solutions that can integrate disparate data sources with no limit to type or volume quickly. Equally crucial is support for global data sover eignty regulations and robust metadata creation for easy data identifica tion and understanding. Real-time analytics are essential to enable timely actions and scale busi ness success. Build A Compelling Business Case Gain an up-to-date understanding of your data estate, usage, and compliance environ ments. This reveals inef ficiencies, such as data duplication impacting IT spend, and establishes a baseline for improve ment by pinpointing fragmentation. Collaborate with cross-functional leaders to directly link the data strategy to tangible busi ness outcomes. Assess total cost of ownership (TCO), beyond initial technology costs, factors in ongoing expenses like process redesign, gover nance tools, and cloud infrastructure to build a compelling case for long term ROI and prevent any surprises. Data Management Is The Path Forward Metadata management is emerging as a power ful solution, automating data governance, and making data more ac cessible. This approach accelerates time-to-value by providing unified data intelligence. Organizations that embrace a holistic ap proach to data man agement will be best positioned to unlock unprecedented value. By fostering a data-driven culture, investing in robust data management and governance frame works, enterprises will be better positioned to deliver exceptional cus tomer experiences.

Why Knowledge Graphs Are The Future Of Data Intelligence Platforms
Why Knowledge Graphs Are The Future Of Data Intelligence Platforms

Forbes

time6 days ago

  • Business
  • Forbes

Why Knowledge Graphs Are The Future Of Data Intelligence Platforms

Rajiv Shesh is the Chief Revenue Officer at HCLSoftware where he leads revenue growth & customer advocacy for Products & Platforms division. What's really powering AI? High-quality data—foundational to creating new products and solutions. With AI adoption reaching a tipping point, the emergence of AI use cases has enforced a paradigm shift toward high-quality, trustworthy data, essential building blocks crucial for scalable and reliable AI solutions. According to a GenAI Data Readiness survey, 44% of organizations surveyed said they are deploying GenAI for critical use cases, but only 4% are confident about their data preparation. Without a trusted data foundation, organizations run the risk of building solutions that deliver inaccurate or misleading results known as hallucinations, leading to poor code, confusion, compliance violations and costly fines. For example, a financial analyst using mislabeled data can produce flawed forecasts that cascade into poor decision making and substantial losses for end users. Similarly, in healthcare, outdated datasets can lead to misdiagnoses, triggering lawsuits and regulatory fines. The Future Of Data Management Is Graph-Powered In times of blink-and-miss-it AI breakthroughs, it's clear that the secret sauce lies in architecting an effective data management stack with data quality, reliability and speed at the core. But traditional non-graph-powered data management solutions often fall short of keeping pace with evolving business needs and struggle with static, big metamodels that are often difficult to implement and rarely see user adoption. Enter knowledge-graph-powered data intelligence platforms with metadata management capabilities. Google popularized the term "knowledge graph" in this 2012 blog post. Since then, there has been a massive momentum around knowledge graphs, which have become increasingly vital in data intelligence platforms by providing structured, interconnected representations of data that go beyond tabular formats. Think of knowledge-graph-powered data catalogs as the search engine for the data in the enterprise. It empowers business users to move beyond static tables and columns that fail to capture relationships between data assets and visualize their enterprise data landscape like a map. Instead of combing through hundreds of thousands of tables and columns, data users can visually navigate their enterprise's data landscape and get precise results instantly through natural language interactions. Tapping Into The Federated Knowledge Graph Advantage In today's enterprise environment, AI-critical data is distributed across multiple systems—from cloud applications to legacy on-premises infrastructure. To overcome data silos, traditional centralized knowledge graphs consolidate data into a single repository. However, this approach increases data movement, introduces latency and creates governance complexities. On the other hand, federated knowledge graphs address data silos by bringing a decentralized approach to data integration. Unlike traditional centralized knowledge graphs that require consolidating data into a single repository, federated knowledge graphs operate across multiple, distributed data sources while maintaining a unified semantic layer. Also, the federated approach reduces the need for extensive data movement, enhances data governance and provides faster, real-time access to information. By connecting data from disparate systems through a federated graph, enterprises can get a holistic, contextual view of their data landscape without compromising agility, empowering business users with richer insights. Federated Knowledge Graph Use Cases Here's a look at a few use cases across industries. Retail companies are data-rich and have a huge variety of data, from customer service tools, sales records, POS systems and e-commerce platforms residing across various platforms, making it difficult to analyze. Through a federated graph, customers can connect data from disparate sources seamlessly without data consolidation. By adding a semantic layer, even non-technical users can use simple terms such as 'customer satisfaction scores' or 'total sales in the previous quarter' to get more meaningful and relevant results when searching for the best data products across the enterprise to do correlation analysis on. Similarly, in the healthcare segment, federated graphs help keep sensitive patient data secure while enabling cross-institutional insights through a unified semantic layer. The decentralized model ensures compliance with regulations by allowing data to remain under local control, in keeping with data residency mandates. Additionally, it also facilitates the integration of diverse patient records and clinical research data, providing GenAI models with the contextual knowledge needed to create personalized treatment plans. To function precisely, these models need context. Nothing is stronger than a knowledge graph to deliver that context with ontological robustness. It makes the GenAI models work securely with verified information, reducing hallucination risks. Simultaneously, GenAI updates these knowledge graphs by analyzing new research and patient data to ensure the accuracy and relevancy of results. In financial services, real-time fraud detection across multiple systems can be done without moving sensitive data by leveraging data intelligence platforms with federated knowledge graphs, which can identify transaction patterns in real time, ultimately reducing financial risks. Essential Features To Consider When evaluating solutions, chief data officers need to understand how well these platforms support distributed governance and cross-system collaboration without compromising agility. A data intelligence platform with a federated knowledge graph approach enables distributed data governance while maintaining central oversight, addressing key challenges in modern data management. Unlike traditional data lakes or warehouses that require extensive data movement, leading to latency and governance risks, federated knowledge graphs allow data to remain localized, respecting data residency and security requirements. They also surpass data catalog-only solutions by capturing semantic relationships between data assets, providing deeper context and more meaningful insights. Additionally, it helps avoid data silos, fostering interoperability across diverse systems and partners. Forbes Business Development Council is an invitation-only community for sales and biz dev executives. Do I qualify?

HCLSoftware Announces Commitment to Saudi Vision 2030 in Riyadh - Middle East Business News and Information
HCLSoftware Announces Commitment to Saudi Vision 2030 in Riyadh - Middle East Business News and Information

Mid East Info

time28-01-2025

  • Business
  • Mid East Info

HCLSoftware Announces Commitment to Saudi Vision 2030 in Riyadh - Middle East Business News and Information

HCLSoftware launches a new Total Experience platform; aims to empower citizen engagement, drive economic diversification, develop national talent, and promote sustainability. HCLSoftware, a global leader in enterprise software solutions, announced today the company's commitment to Saudi Vision 2030. HCLSoftware leaders presented their declaration today during an Executive Summit in Riyadh with the launch of HCLSoftware's new Total Experience (TX) platform. Saudi Arabia's Vision 2030 is a strategic plan that uses technology to transform the country's economy and improve the lives of its citizens. The plan focuses on artificial intelligence (AI), the internet of things (IoT), and digital infrastructure. 'HCLSoftware is committed to supporting Saudi Vision 2030 by unlocking transformative growth through an innovative platform of digital solutions,' said Rajiv Shesh, Chief Revenue Officer, HCLSoftware. 'Saudi Arabia's Vision 2030, especially their Deep Tech Ecosystem, falls squarely in HCLSoftware's definition of the future.' HCLSoftware's Total Experience is a holistic approach that considers every touchpoint an organization has with its customers and employees, ensuring every interaction is intelligent, connected, immersive and personalized. The platform aligns well with the mission of Saudi Vision 2030 in many ways. Another key aspect of Saudi Arabia's Vision 2030 aims to integrate and empower women into various fields, including technology. In line with Saudi Arabia's vision 2030 HCLSoftware will promote STEM education, foster entrepreneurship, and implement supportive government policies to cultivate a dynamic and inclusive tech ecosystem. This transformative vision not only equips women with the necessary skills and resources to thrive but also cultivates a cultural shift that embraces and celebrates their invaluable contributions to the nation's technological advancement and economic prosperity. 'Vision 2030 brings in encouraging policies, cutting-edge R&D, and access to deep tech talents – combining these with our offerings, like Total Experience, will lead towards engaging digital transformation projects,' said Kalyan Kumar, Chief Product Officer, HCLSoftware.

HCLSoftware announces commitment to Saudi Vision 2030 in Riyadh
HCLSoftware announces commitment to Saudi Vision 2030 in Riyadh

Zawya

time27-01-2025

  • Business
  • Zawya

HCLSoftware announces commitment to Saudi Vision 2030 in Riyadh

NOIDA, India & SANTA CLARA, Calif.- -(BUSINESS WIRE)-- HCLSoftware, a global leader in enterprise software solutions, announced today the company's commitment to Saudi Vision 2030. HCLSoftware leaders presented their declaration today during an Executive Summit in Riyadh with the launch of HCLSoftware's new Total Experience (TX) platform. Saudi Arabia's Vision 2030 is a strategic plan that uses technology to transform the country's economy and improve the lives of its citizens. The plan focuses on artificial intelligence (AI), the internet of things (IoT), and digital infrastructure. 'HCLSoftware is committed to supporting Saudi Vision 2030 by unlocking transformative growth through an innovative platform of digital solutions,' said Rajiv Shesh, Chief Revenue Officer, HCLSoftware. 'Saudi Arabia's Vision 2030, especially their Deep Tech Ecosystem, falls squarely in HCLSoftware's definition of the future.' HCLSoftware's Total Experience is a holistic approach that considers every touchpoint an organization has with its customers and employees, ensuring every interaction is intelligent, connected, immersive and personalized. The platform aligns well with the mission of Saudi Vision 2030 in many ways. Another key aspect of Saudi Arabia's Vision 2030 aims to integrate and empower women into various fields, including technology. In line with Saudi Arabia's vision 2030 HCLSoftware will promote STEM education, foster entrepreneurship, and implement supportive government policies to cultivate a dynamic and inclusive tech ecosystem. This transformative vision not only equips women with the necessary skills and resources to thrive but also cultivates a cultural shift that embraces and celebrates their invaluable contributions to the nation's technological advancement and economic prosperity. 'Vision 2030 brings in encouraging policies, cutting-edge R&D, and access to deep tech talents – combining these with our offerings, like Total Experience, will lead towards engaging digital transformation projects,' said Kalyan Kumar, Chief Product Officer, HCLSoftware. About HCLSoftware HCLSoftware fuels the Digital+ economy by developing, marketing, selling and supporting solutions in four key areas: digital transformation; data and analytics; AI and intelligent automation and enterprise security. HCLSoftware drives customer success through relentless product innovation for more than 20,000 organizations, including a majority of the Fortune 100 and almost half of the Fortune 500.

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