Maximizing the data lake investment

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Organizations are constantly looking for better ways to turn data into insights, which is why many government agencies are now exploring the concept of data lakes. Data lakes combine distributed storage with rapid access to data, which can allow for faster analysis than more traditional methods such as enterprise data warehouses. Data lakes are special, in part, because they provide business users with direct access to raw data without significant IT involvement. This "self-service" access lets users quickly analyze data for insights. Because they store the full spectrum of an enterprise's data, data lakes can break down the challenge of data silos that often bedevil data users.



Informatica Announces Enterprise Data Catalog Integrations With Microsoft, Tableau, and Databricks - insideBIGDATA

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Informatica, the enterprise cloud data management leader, announced the industry's most comprehensive enterprise-scale intelligent data catalog, enhanced with technology innovations and tight strategic-partner integrations. The Informatica Enterprise Data Catalog (EDC) creates a "catalog of catalogs" with AI-driven data discovery across multi-cloud and hybrid environments, providing broad metadata connectivity to support organizations in driving their data-driven digital transformations. By enabling easy discovery and understanding of data across the enterprise, the Informatica EDC allows enterprises to fully leverage their data for greater business insights and value. In addition, expanded integrations with Tableau, and new EDC metadata scanners for Delta Lake, the open source project from Databricks, and Microsoft Azure Data Lake Storage Gen2, further enable Informatica EDC customers to build a strategic approach to analytics modernization. "As the strategic importance of enterprise data grows, data cataloging has become a foundational requirement for successful analytics initiatives, which is confirmed by the 110 percent year-over-year growth in Informatica's EDC customer base," said Ronen Schwartz, senior vice president and general manager, data integration, big data, and cloud, Informatica.


Gartner Identifies Top 10 Data and Analytics Technology Trends for 2019

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Augmented analytics, continuous intelligence and explainable artificial intelligence (AI) are among the top trends in data and analytics technology that have significant disruptive potential over the next three to five years, according to Gartner, Inc. Speaking at the Gartner Data & Analytics Summit in Sydney today, Rita Sallam, research vice president at Gartner, said data and analytics leaders must examine the potential business impact of these trends and adjust business models and operations accordingly, or risk losing competitive advantage to those who do. "The story of data and analytics keeps evolving, from supporting internal decision making to continuous intelligence, information products and appointing chief data officers," she said. "It's critical to gain a deeper understanding of the technology trends fueling that evolving story and prioritize them based on business value." According to Donald Feinberg, vice president and distinguished analyst at Gartner, the very challenge created by digital disruption -- too much data -- has also created an unprecedented opportunity. The vast amount of data, together with increasingly powerful processing capabilities enabled by the cloud, means it is now possible to train and execute algorithms at the large scale necessary to finally realize the full potential of AI. "The size, complexity, distributed nature of data, speed of action and the continuous intelligence required by digital business means that rigid and centralized architectures and tools break down," Mr. Feinberg said.


Is your data ready for AI? Part 1

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Artificial intelligence is a major driver of value for the enterprise. According to a recent AI study from IBM, 82 percent of organizations are now at least considering AI adoption, and the number of companies that are beyond the AI implementation stage is 33 percent higher than it was in 2016. What's more, by pairing AI with other exponential technologies such as automation, blockchain and the Internet of Things (IoT), companies are redefining their business architectures. The IBM "Cognitive Enterprise" report highlights how these technologies represent the next inflection point for the enterprise comparable in scale and scope to the introduction of the Internet and mobile technology. The cognitive enterprise is a framework for companies to define and pursue a bold vision to realize new sources of value and restructure their industries, missions, and business models.