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6 Case Studies on The Benefits of Business Intelligence And Analytics

datapine

Using business intelligence and analytics effectively is the crucial difference between companies that succeed and companies that fail in the modern environment. Experience the power of Business Intelligence with our 14-days free trial! Why Is Business Intelligence So Important?

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The Role Of Data Warehousing In Your Business Intelligence Architecture

datapine

In this post, we will explain the definition, connection, and differences between data warehousing and business intelligence , provide a BI architecture diagram that will visually explain the correlation of these terms, and the framework on which they operate. What Is Data Warehousing And Business Intelligence?

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Business Intelligence for Fairs, Congresses and Exhibitions

Smart Data Collective

While different companies, regardless of their size, have different operational processes, they share a common need for actionable insight to drive success in their business. Advancement in big data technology has made the world of business even more competitive. This eliminates guesswork when coming up with business strategies.

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Best Practices for Metadata Management

Alation

What Is Metadata? Metadata is information about data. A clothing catalog or dictionary are both examples of metadata repositories. Indeed, a popular online catalog, like Amazon, offers rich metadata around products to guide shoppers: ratings, reviews, and product details are all examples of metadata.

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What is a business intelligence analyst? A key role for data-driven decisions

CIO Business Intelligence

Business intelligence (BI) analysts transform data into insights that drive business value. What does a business intelligence analyst do? The role is becoming increasingly important as organizations move to capitalize on the volumes of data they collect through business intelligence strategies.

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Run Apache XTable in AWS Lambda for background conversion of open table formats

AWS Big Data

Central to a transactional data lake are open table formats (OTFs) such as Apache Hudi , Apache Iceberg , and Delta Lake , which act as a metadata layer over columnar formats. In practice, OTFs are used in a broad range of analytical workloads, from business intelligence to machine learning.

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The state of data quality in 2020

O'Reilly on Data

These include the basics, such as metadata creation and management, data provenance, data lineage, and other essentials. They’re still struggling with the basics: tagging and labeling data, creating (and managing) metadata, managing unstructured data, etc. They don’t have the resources they need to clean up data quality problems.