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Breaking State and Local Data Silos with Modern Data Architectures

Cloudera

It outlines a scenario in which “recently married people might want to change their names on their driver’s licenses or other documentation. That should be easy, but when agencies don’t share data or applications, they don’t have a unified view of people. Towards Data Science ). Forrester ). Gartner ).

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Data Mesh 101: How Data Mesh Can Be Used in an Organization

Ontotext

This calls for additional planning, documentation, and testing. A data mesh will likely require more engineers to get started, so a critical mass is needed for successful adoption. Each team should be accountable for providing their prepared data sets to downstream systems. For instance, JPMorgan Chase & Co.

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CIOs rise to the ESG reporting challenge

CIO Business Intelligence

“Always the gatekeepers of much of the data necessary for ESG reporting, CIOs are finding that companies are even more dependent on them,” says Nancy Mentesana, ESG executive director at Labrador US, a global communications firm focused on corporate disclosure documents. Most companies find themselves in a similar situation.

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Get Your Analytics Insights Instantly – Without Abandoning Central IT

Cloudera

Storing data in a proprietary, single-workload solution also recreates dangerous data silos all over again, as it locks out other types of workloads over the same shared data. The Data Lake service in Cloudera’s Data Platform provides a central place to understand, manage, secure, and govern data assets across the enterprise.

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

erwin

Once you’ve determined what part(s) of your business you’ll be innovating — the next step in a digital transformation strategy is using data to get there. Constructing A Digital Transformation Strategy: Data Enablement. Many organizations prioritize data collection as part of their digital transformation strategy.

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What Is a Data Catalog?

Alation

Figure 1 illustrates the typical metadata subjects contained in a data catalog. Figure 1 – Data Catalog Metadata Subjects. Datasets are the files and tables that data workers need to find and access. They may reside in a data lake, warehouse, master data repository, or any other shared data resource.

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The Value is in the Data (Wrangling)

Darkhorse

So what is data wrangling? Let’s imagine the process of building a data lake. First off, data wrangling is gathering the appropriate data. (By Once you’ve documented and understood your sources, you have reached the second stage: data sloughs (note, you have more than one). By human or machine?)