Enterprise data warehouse management
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Machine Learning Meets Data Quality
Read an exclusive interview with Andrew Burt, chief privacy offer and legal engineer at Immuta Inc., on data governance and machine learning integration. Plus, uncover steps IT managers are taking to improve data quality in their big data environments in order to ensure analytics accuracy.
Enterprise data warehouse management News
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March 21, 2019
21
Mar'19
Machine learning approaches gain critical mass for data pros
Machine learning will bring change to analytics and data management, said data luminary Michael Stonebraker. Others agree managing such change will take special effort.
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March 20, 2019
20
Mar'19
Aparavi update adds better data classification, more clouds
Aparavi updates Active Archive with customizable data classification and tagging capabilities for easier future retrieval and improved metadata search.
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March 15, 2019
15
Mar'19
Big data management practices gain attention amid risks
Many data professionals have yet to solidify traditional data management practices, but they have a new set of challenges to overcome to ensure data privacy and avoid misuse.
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March 12, 2019
12
Mar'19
Aerospike database garners Spark, Kafka connectors
Apache Kafka and Apache Spark connectors ease use of the Aerospike NoSQL data store in high-speed applications such as analytics that are becoming more broadly supported.
Enterprise data warehouse management Get Started
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DataOps is more than DevOps for data, Delphix CTO says
Data operations is young compared to DevOps, but it is increasingly used as part of projects that put data at the center of development. Here, Delphix CTO Eric Schrock makes observations about the trend. Continue Reading
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data analytics (DA)
Data analytics (DA) is the science of examining raw data with the purpose of drawing conclusions about that information. Continue Reading
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Tips for creating curated data sets for self-service BI users
Data curation initiatives can help streamline BI processes by reducing the amount of time users spend locating and preparing data. Get four tips for preparing data sets. Continue Reading
Evaluate Enterprise data warehouse management Vendors & Products
Weigh the pros and cons of technologies, products and projects you are considering.
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Augmented data management draws more enterprise interest
With AI and machine learning, organizations are starting to augment their data management. This is changing the way enterprise users capture, govern and integrate data. Continue Reading
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Explore Hadoop distributions to manage big data
Discover the uses of Hadoop distributions and the first steps in evaluating these products, as well as how the merger of rivals Cloudera and Hortonworks affects the market. Continue Reading
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Cloud data warehouse makes inroads as users spurn admin tasks
Overlooked in the run-up to Hadoop, data warehouses have found new life off premises. Cloud-based data warehouses find favor with teams that want to reduce warehouse administration. Continue Reading
Manage Enterprise data warehouse management
Learn to apply best practices and optimize your operations.
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Data management trends for 2019: Governance, DataOps, cloud
Better data governance, increased cloud use and wider DataOps adoption head the list of trends for data management teams to plan for in 2019, IT analysts say. Continue Reading
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How to build a master data index: Static vs. dynamic indexing
Expert David Loshin explores the differences between static and dynamic indexing in master data management systems, and which queries each approach can support. Continue Reading
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Big data platform broadens place in analytics architecture
Big data platforms stumbled a bit getting out of the prototyping stage. But a view from the Strata Data Conference in New York sees broader use in the offing. Continue Reading
Problem Solve Enterprise data warehouse management Issues
We’ve gathered up expert advice and tips from professionals like you so that the answers you need are always available.
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Four first steps for customer data management
Forrester's Mike Gualtieri details how to develop a unified plan to manage customer data that gives business users what they need to manage CRM programs. Continue Reading
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What's the difference between DDL and DML?
What's the difference between DDL and DML? Get the answer and see examples of data manipulation language and data definition language commands for SQL databases. Continue Reading
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Data integration techniques to help keep BI data consistent
Data integration processes that aren't managed properly can create inconsistent data in BI and analytics applications. Here are some steps to avoid that problem. Continue Reading