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The Future of the Data Lakehouse – Open

Cloudera

These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. In recent years, the term “data lakehouse” was coined to describe this architectural pattern of tabular analytics over data in the data lake.

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Introducing watsonx: The future of AI for business

IBM Big Data Hub

At IBM, we believe it is time to place the power of AI in the hands of all kinds of “AI builders” — from data scientists to developers to everyday users who have never written a single line of code. With watsonx.data , businesses can quickly connect to data, get trusted insights and reduce data warehouse costs.

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How DataOps is Transforming Commercial Pharma Analytics

DataKitchen

New data is shared with users by updating reporting schema several times a day. The architecture takes purpose-built data warehouses /marts and other forms of aggregation and star views tailored to analyst requirements. The DataOps Platform does not replace a data lake or the data hub. It’s that simple. .

Analytics 246
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How OLAP and AI can enable better business

IBM Big Data Hub

Initially, they were designed for handling large volumes of multidimensional data, enabling businesses to perform complex analytical tasks, such as drill-down , roll-up and slice-and-dice. Early OLAP systems were separate, specialized databases with unique data storage structures and query languages.

OLAP 59
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Fivetran Modern Data Stack Conference 2023: Key Takeaways

Alation

Practitioners and hands-on data users were thrilled to be there, and many connected as they shared their progress on their own data stack journeys. People were familiar with the value of a data catalog (and the growing need for data governance ), though many admitted to being somewhat behind on their journeys.

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Constructing A Digital Transformation Strategy: Putting the Data in Digital Transformation

erwin

Part Two of the Digital Transformation Journey … In our last blog on driving digital transformation , we explored how enterprise architecture (EA) and business process (BP) modeling are pivotal factors in a viable digital transformation strategy. Constructing A Digital Transformation Strategy: Data Enablement.

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Centralize Your Data Processes With a DataOps Process Hub

DataKitchen

When the tests pass, the orchestration admits the data to a data catalog. New data is shared with users by updating reporting schema several times a day. This delivery takes the form of purpose-built data warehouses/marts and other forms of aggregation and star views tailored to analyst requirements.