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The Many Faces of Metadata Management

tdwi.org

Few things bring down the value of data faster than confusion and uncertainty about what it is, where it came from, and whether it is good quality data. Yet as more users seek to access and interact with data and reports for business intelligence and analytics and as data sources become larger and more varied, confusion and uncertainty spread fast. Executives, managers, regulatory administrators, and other key personnel cannot rely on their reports, KPIs, and dashboards. Users cannot even find reports that the organization is producing. Instead, users spend more of their time trying to locate data and reports and correcting mistakes than they do applying data insights to solve business problems.
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Spotlight

Automated Code Translation Engine

SHIFT is an Automated Code Translation Engine that automates the conversion of legacy code into various target languages, to run natively inside of Big Data environments, including Hadoop, Spark, R and in the Cloud. SHIFT can accelerate the translation of up to 80% of the most complex code, and the output is always consistent, ensuring compliance with industry coding standards. SHIFT allows organizations to minimize the cost and manual effort involved in many migration-oriented projects, including decommissioning and migrating an enterprise data warehouse to a data lake, source system rationalization, or modernizing legacy ETLs. SHIFT supports several different source and target languages and based on its continuous learning functionality, it increases the scope of automation over time. SHIFT is the only tool to help accelerate that journey.

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The Rise of Data Mesh and Data Fabric Architectures

As businesses strive to advance digital transformation efforts, legacy architectures can be a significant obstacle to enabling the agility required to succeed in today's ever-changing data landscape. Many enterprises struggle with scaling the delivery of data and analytics to accommodate the growing array of data domains, users, and use cases. As a result, data mesh and data fabric architectures are on the rise with the aim of abstracting data management complexity, increasing data availability, and fostering greater collaboration.
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Join Datavative and The Johnson Firm to learn how law firms of all sizes leverage the Domo platform to manage and optimize productivity and case management. No matter if you are a plaintiff firm, defense firm, corporate firm, or retail firm, Domo will help you increase revenue while decreasing expenses.
Watch Now

How to Gauge Project Feasibility with Rapid Prototyping using Code-First Data Science

Data scientists’ time is valuable. Computing resources are expensive. With only 87% of projects ever making it to production (Source: VentureBeat), organizations often overcommit to costly projects that bear little fruit. Data science teams need a way to assess project feasibility without diving head first.
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More On-Demand Webinars

Spotlight

Automated Code Translation Engine

SHIFT is an Automated Code Translation Engine that automates the conversion of legacy code into various target languages, to run natively inside of Big Data environments, including Hadoop, Spark, R and in the Cloud. SHIFT can accelerate the translation of up to 80% of the most complex code, and the output is always consistent, ensuring compliance with industry coding standards. SHIFT allows organizations to minimize the cost and manual effort involved in many migration-oriented projects, including decommissioning and migrating an enterprise data warehouse to a data lake, source system rationalization, or modernizing legacy ETLs. SHIFT supports several different source and target languages and based on its continuous learning functionality, it increases the scope of automation over time. SHIFT is the only tool to help accelerate that journey.

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