A good data visual can provide a very fast construct of a situation or trend – useful when you have a large, complex dataset or information that isn’t joined or connected. There are many types of data visualizations available. Which is the right one for your use case?

Your business needs actionable insights from your Oracle ERP data to respond to volatile market conditions and outpace your competition. But generating custom reports requires deep technical knowledge and the process is often managed by IT. The process can often take weeks, if not months, and, in many cases, the report or dashboard is limited to a single use case and applicable only to a single business unit or user – often only the requester.

In its 2022 Magic Quadrant™ for Data Quality Solutions report, Gartner® emphasizes the “importance of having a critical approach toward managing the health and fitness of data.” We agree that “poor data quality completely destroys business value.” Organizations simply cannot afford for data quality to be an afterthought. And if you’re currently in the process of evaluating data solutions for your organization, this report can help.

BigQuery’s impressive performance reduces processing time from months to hours and delivers on-demand real-world insights for Telus.

Yellowfin analytics has a broad range of capabilities to help enterprise organizations and product owners solve the most pressing analytical dashboards and reporting needs. If you've been using Yellowfin for a while, you know how great it is to tell stories with data, work together, and make beautiful, easy-to-use dashboards that let more people see, understand, and act on their data.

Whether you call it self-service analytics or self-service business intelligence (BI), there has been much discussion about the perils, myths, promises, and prospects of successfully building self-service capability. Going forward, I’ll use the phrase “self-service BI” but you are welcome to substitute the words “self-service analytics”.So, is self-service BI actually attainable or just snake oil?

Cloudera has been working on Apache Ozone, an open-source project to develop a highly scalable, highly available, strongly consistent distributed object store. Ozone is able to scale to billions of objects and hundreds petabytes of data. It enables cloud-native applications to store and process mass amounts of data in a hybrid multi-cloud environment and on premises.

Are legacy systems and information silos helping or hindering you from getting the most from your data? A TDWI Research report suggests it may be time to rethink your data architecture.

As data science and machine learning adoption has grown over the last few years, Python is catching up to SQL in popularity within the world of data processing. SQL and Python are both powerful on their own, but their value in modern analytics is highest when they work together.

Snowflake is committed to helping developers focus on building their apps and businesses rather than on infrastructure management. At this year’s Snowday, Snowflake announced a series of advancements that empower developers to do more with their data, enhancing productivity and unlocking new ways to develop applications, pipelines, and machine learning (ML) models with Snowflake’s unified data platform.