Remove Business Intelligence Remove Metadata Remove Optimization Remove Structured Data
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Do I Need a Data Catalog?

erwin

Organizations with particularly deep data stores might need a data catalog with advanced capabilities, such as automated metadata harvesting to speed up the data preparation process. Three Types of Metadata in a Data Catalog. Technical Metadata. Operational Metadata.

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Building a Beautiful Data Lakehouse

CIO Business Intelligence

As a result, users can easily find what they need, and organizations avoid the operational and cost burdens of storing unneeded or duplicate data copies. Newer data lakes are highly scalable and can ingest structured and semi-structured data along with unstructured data like text, images, video, and audio.

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What is data governance? Best practices for managing data assets

CIO Business Intelligence

The Business Application Research Center (BARC) warns that data governance is a highly complex, ongoing program, not a “big bang initiative,” and it runs the risk of participants losing trust and interest over time. The program must introduce and support standardization of enterprise data.

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What is a data scientist? A key data analytics role and a lucrative career

CIO Business Intelligence

As such, a data scientist must have enough business domain expertise to translate company or departmental goals into data-based deliverables such as prediction engines, pattern detection analysis, optimization algorithms, and the like. Semi-structured data falls between the two.

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Top 10 Key Features of BI Tools in 2020

FineReport

Nowadays, the business intelligence market is heating up. Both the investment community and the IT circle are paying close attention to big data and business intelligence. Overall, as users’ data sources become more extensive, their preferences for BI are changing. Metadata management.

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Why Your Data Lineage is Incomplete Without an Automated Business Glossary

Octopai

Although it was only one of many Mars mission failures in the history of space travel, it was one that easily could have been prevented by achieving the optimal set of equipment and communication to power space travel. . Moreover, others need to trace data history, get its context to resolve an issue before it actually becomes an issue.

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How smava makes loans transparent and affordable using Amazon Redshift Serverless

AWS Big Data

To create and manage the data products, smava uses Amazon Redshift , a cloud data warehouse. In this post, we show how smava optimized their data platform by using Amazon Redshift Serverless and Amazon Redshift data sharing to overcome right-sizing challenges for unpredictable workloads and further improve price-performance.