Data analytics
New & Notable
Free Guide: 5 Data Science Tools to Consider
With the right data science tools, you can gain powerful insight out of the ever-growing pools of corporate data. Learn why data science experts are using Python, R, Jupyter Notebook, Tableau, and Keras.
Data analytics News
-
December 09, 2019
09
Dec'19
BI vendors jump into low-code/no-code tools for developers
A spate of BI vendors included easy-to-use tools for developers in their recent updates, perhaps marking the start of a new trend in the analytics software market.
-
December 03, 2019
03
Dec'19
Sisense analytics platform update features AI, data prep tool
Augmented intelligence features and an in-warehouse data prep tool highlight Sisense's latest update, its second since acquiring Periscope Data in May.
-
December 02, 2019
02
Dec'19
Operation Fistula uses data to treat childbirth injuries
Aided by an analytics stack developed by Exasol, nonprofit Operation Fistula is working to end obstetric fistula in targeted regions around the world.
-
December 02, 2019
02
Dec'19
The technological evolution of IT industry leaders: 2000 - 2020
As technology has shifted since 2000, so have IT leaders. This guide looks at how Oracle, Cisco, Dell and SAP have adapted to emerging technologies and are preparing for 2020.
Data analytics Get Started
Bring yourself up to speed with our introductory content
-
Financial business analytics transforms numbers into gold
AI-driven business analytics provides finance departments with the tools to exercise more influence over corporate strategy, but only with the right skills and training. Continue Reading
-
AI, blockchain and IoT convergence improves daily applications
IT pros may find IoT, blockchain and AI difficult to conceptualize as individual technologies, but together, the three can generate data, improve analysis and establish trust. Continue Reading
-
chief data officer (CDO)
A chief data officer (CDO) is a C-level executive who is responsible for an organization's data use and data governance. Continue Reading
Evaluate Data analytics Vendors & Products
Weigh the pros and cons of technologies, products and projects you are considering.
-
Automated tools broaden the future scope of data science
Automated data science tools may make their way into the data science process, but are unlikely to ever be able to do everything human data scientists do, experts say. Continue Reading
-
AI-driven development trends shake up the cloud market
Enterprises are increasingly interested in AI, and cloud vendors are in a race to adapt their platforms to meet those needs. See what initiatives are underway to meet the next wave of app development. Continue Reading
-
Data visualization in machine learning boosts data scientist analytics
Data scientists offer practical insights into the role of visualization tools in building, exploring, deploying and monitoring their machine learning models. Continue Reading
Manage Data analytics
Learn to apply best practices and optimize your operations.
-
Predictive storage analytics and AI make storage smarter
Intelligent storage is all the rage. Discover how predictive analytics for storage, AI and machine learning makes storage infrastructure more flexible and cost effective. Continue Reading
-
Compliance analytics helps data storage meet PII standards
Organizations are using predictive analytics and AI to sift through large data sets to ensure that any data stored is compliant with all personally identifiable information rules. Continue Reading
-
NLP makes augmented data discovery a reality in analytics
BI vendors are increasingly using NLP technology to make their products work more like a web search, with simplified user interfaces and improved ease of use for customers. Continue Reading
Problem Solve Data analytics Issues
We’ve gathered up expert advice and tips from professionals like you so that the answers you need are always available.
-
How to create a data set for machine learning with limited data
A shortage of data for machine learning training sets can halt a company's AI development in its tracks. Turning to external sources and hidden data can solve the problem. Continue Reading
-
7 steps to a successful data lake implementation
Flooding a Hadoop cluster with data that isn't well organized and managed can stymie analytics efforts. Take these steps to help make your data lake accessible and usable. Continue Reading
-
Storing predictive analytics data can be tricky: Avoid these 5 errors
Looking into the future is getting easier with predictive analytics, but only when your storage resources are able to meet the demanding needs of the data those tools generate. Continue Reading