Big data management

Big data management is the organization, administration and governance of large volumes of both structured and unstructured data.. See complete definition.

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Databases vs. Data Warehouses vs. Data Lakes vs. Data Marts

This cheat sheet will help you better understand how each repository differs based on the type, purpose and quality of data. Plus, you’ll get an introduction to the features of data catalog software, a user-friendly metadata management system.

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Big data management News

March 04, 2020 04 Mar'20
Microsoft boosts Azure big data strategy with Hadoop distro

Microsoft Azure's HDInsight has a new, company-backed distribution of Hadoop, which should reassure customers interested in hybrid big data deployments.
February 25, 2020 25 Feb'20
Databricks Data Ingestion Network brings data to lakehouse

Databricks Ingest entered a public preview in a move by Databricks to enable a lakehouse that combines the best features of the data lake and data warehouse models.
January 14, 2020 14 Jan'20
Former Hortonworks leader named new Cloudera CEO

Cloudera finds a new leader, pulling the former CEO of Hortonworks back into the fold to help set the direction for the big data Hadoop vendor as it moves forward in 2020.
December 18, 2019 18 Dec'19
Q&A: The challenges of cloud-native data management

Cloud native data management isn't usually the first thing on anyone's mind, acknowledges Portworx co-founder and CTO Goutham Rao -- but find out how it's become part of organizations' journey.

Big data management Get Started

Bring yourself up to speed with our introductory content

How to handle data management in the cloud

Managing data in the cloud can result in cost and management complexities. But you can also use the technology to get a deeper understanding of your data. Continue Reading
Data warehousing design and value change with the times

Big data, the cloud and analytics profoundly shape data warehouse purpose and design. Learn how companies derive value from a repository that at times needs definition. Continue Reading
What is data management and why is it important?

Data management is the process of ingesting, storing, organizing and maintaining the data created and collected by an organization, as explained in this in-depth look at the process. Continue Reading

Evaluate Big data management Vendors & Products

Weigh the pros and cons of technologies, products and projects you are considering.

3 of the top use cases for graph databases

Graph databases establish many unique relationships between data points. These unusual relationships are beneficial in many use cases, but here are the top three. Continue Reading
NoSQL database comparison to help you choose the right store

With so many NoSQL databases to choose from, how can you tell which is best for your data set? Check out this comparison of some of the most popular NoSQL databases. Continue Reading
Evaluating the different types of DBMS products

The various types of database software come with advantages, limitations and optimal uses that prospective buyers should be aware of before choosing a DBMS. Continue Reading

Manage Big data management

Learn to apply best practices and optimize your operations.

How to build an effective streaming data architecture

Data architecture can be tricky when it comes to real-time analytics. Clear objectives and scalability are important factors when determining the streaming data architecture you need. Continue Reading
3 cloud-based data management challenges

Your organization has data in the cloud, but there are still concerns as to how you and your data protection vendor manage that data to maintain performance and costs. Continue Reading
6 best practices on data governance for big data environments

Efforts to govern big data must corral a mix of structured and unstructured data. That's a challenge for most organizations. These six action items will help. Continue Reading

Problem Solve Big data management Issues

We’ve gathered up expert advice and tips from professionals like you so that the answers you need are always available.

What data lake governance challenges do organizations face?

Consultant Anne Marie Smith details five challenges that an organization may face in applying data governance policies to data lakes and offers advice on how to overcome them. Continue Reading
Breaking down data silos with strong data governance

Not having a single source of truth can be a huge issue for data professionals. But strong data governance policies can prevent data silos and lead to better-quality data. Continue Reading
Proactive practices for data quality improvement

Instead of waiting for data quality to become an issue, consider a proactive approach. Here are ways to improve data quality in your organization before it's a problem. Continue Reading