Data warehouse News
February 13, 2018
This is a guest blogpost by Dave Wells, practice director, data management at Eckerson Group. If there’s one thing the IT industry is exceptionally good at it, it’s proclaiming the death of a ...
February 05, 2018
Why did Snowflake Computing call itself Snowflake Computing? Was it because its founders are snowflake generation kids who are incapable of taking a few hard knocks here and there? Um, ah no, it’s ...
January 03, 2018
This is a guest blogpost by Sebastian Darrington, UK MD at Exasol The days of operating a single vendor IT software estate are behind us. Such is the pace of innovation and change, putting all your ...
December 01, 2017
AWS continues to push its Virtual Private Cloud as the new norm for cloud development and deployment, and further limit public internet exposure. AWS PrivateLink enables customers to privately ...
Data warehouse Get Started
Bring yourself up to speed with our introductory content
Hadoop data lakes offer a new home for legacy data that still has analytical value. There are different ways to convert it for use in Hadoop depending on your analytics needs. Continue Reading
You can create SQL Server databases manually, but knowing how to do a scripted database setup is valuable. Here are the steps involved in executing a create database script. Continue Reading
Microsoft has recently added a SQL Database Query editor to its Azure cloud service. Expert Michael Otey walks you through the new T-SQL development process step-by-step. Continue Reading
Evaluate Data warehouse Vendors & Products
Weigh the pros and cons of technologies, products and projects you are considering.
Your choice of a cloud database, data warehouse or data lake depends on the structure of your data and your analysis needs. Follow these guidelines to know which to choose. Continue Reading
A data lake can provide lots of analytics value to an organization. This quiz can tell you if you know what it takes to deploy and manage one; it also contains info to help boost your knowledge. Continue Reading
Data lakes combined with the proper analytics technology are well suited for IoT implementation. Red Hat chief architect James Kirkland explains why. Continue Reading
Manage Data warehouse
Learn to apply best practices and optimize your operations.
In some regards, the term big data management can be viewed as an oxymoron. In fact, oxymorons abound in this industry and society -- virtual reality, artificial intelligence, science fiction and awfully good, the latter of which can apply to the challenges encountered in managing the onslaught of big data from multiple sources. There are countless tools, techniques and practices available for the big data ecosystem to properly gather, mine, prep, store and analyze data and help smooth operations, build marketing campaigns, improve customer service and develop the next new product disruptor. As simplistic as this may sound, it's up to data managers to sort it all out as their data lakes swell beyond capacity.
"The data lake isn't where data goes to die," Gartner analyst Merv Adrian said at the 2017 Pacific Northwest BI & Analytics Summit, "it's where data goes to live."
October's Business Information opens with our editor's note and advice for data managers to move beyond traditional data control to the critical task of improving data quality and delivery -- taking all that raw data and making it useful. Whether for internal or external business use, the demands for instantaneous data access continue to accelerate, spurred on by mobile apps, artificial intelligence (AI), machine learning and internet of things (IoT).
In that vein, our cover story examines companies that use their big data ecosystem to divert data lakes toward developing new strategies, products and revenue streams -- in the process, smashing their old business patterns. In another feature, IoT and machine learning technologies help take the guesswork out of estimated times of arrival for transport companies whose businesses depend on shipping and receiving goods.
Also in this issue, a business intelligence project combined three data warehouses into one to reduce warehouse size by 80% and data load time from several weeks to just days while causing IT staffing problems in the process. In other features, learn how metadata programs can ease mega management woes; semantic technology could be a blessing or curse to AI; companies are gearing up for greater big data management deployments; and all data must be treated equally in the search to find value.Continue Reading
Changes in data management processes -- including self-service data preparation, data lakes and real-time analytics -- create a new landscape in companies, according to analyst Matt Aslett. Continue Reading
The growing use of mobile devices by business users broadens the risk of data inconsistencies, a hazard that an integrated process for managing metadata and master data can help address. Continue Reading
Problem Solve Data warehouse Issues
We’ve gathered up expert advice and tips from professionals like you so that the answers you need are always available.
Fact tables and dimension tables are used together in star schemas to support data analytics applications. But they play different roles and hold different types of data. Continue Reading
Operational data stores and data warehouses both store operational data, but the similarities between them end there -- and they both have a role to play in analytics architectures. Continue Reading
Providers can now do more than analyze past patient data with healthcare BI tools. They can possibly reduce readmissions and assign facility resources with predictive analytics. Continue Reading