Remove Business Intelligence Remove Data Integration Remove Data Science Remove Metadata
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How companies are building sustainable AI and ML initiatives

O'Reilly on Data

In other words, could we see a roadmap for transitioning from legacy cases (perhaps some business intelligence) toward data science practices, and from there into the tooling required for more substantial AI adoption? Data scientists and data engineers are in demand.

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What is data governance? Best practices for managing data assets

CIO Business Intelligence

The program must introduce and support standardization of enterprise data. Programs must support proactive and reactive change management activities for reference data values and the structure/use of master data and metadata.

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Data architecture strategy for data quality

IBM Big Data Hub

The right data architecture can help your organization improve data quality because it provides the framework that determines how data is collected, transported, stored, secured, used and shared for business intelligence and data science use cases.

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Use Amazon Athena to query data stored in Google Cloud Platform

AWS Big Data

Some examples include AWS data analytics services such as AWS Glue for data integration, Amazon QuickSight for business intelligence (BI), as well as third-party software and services from AWS Marketplace. This post demonstrates how to use Athena to run queries on Parquet or CSV files in a GCS bucket.

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Accenture’s Smart Data Transition Toolkit Now Available for Cloudera Data Platform

Cloudera

Today, modern data warehousing has evolved to meet the intensive demands of the newest analytics required for a business to be data driven. Traditional data warehouse vendors may have maturity in data storage, modeling, and high-performance analysis. Consideration of both data & metadata in the migration.

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Data integrity vs. data quality: Is there a difference?

IBM Big Data Hub

When we talk about data integrity, we’re referring to the overarching completeness, accuracy, consistency, accessibility, and security of an organization’s data. Together, these factors determine the reliability of the organization’s data. In short, yes.

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How to Shop for Data?

Data Virtualization

Reading Time: 3 minutes Today, the most innovative and successful organizations leverage data to increase revenue, minimize expenses, and deliver products and services that meet the needs of their customers. To be truly “data-driven,” an organization must view data as more than a byproduct. The post How to Shop for Data?