How to get started with data analytics, improve your data wrangling, and set expectations for data governance in self-service BI.
- By Quint Turner
- December 13, 2016
How much unrefined data may start costing enterprises, why a disruptive business strategy requires data security, and why some enterprises are still unwilling to let go of departmental data silos.
- By Quint Turner
- December 12, 2016
It was hard enough to manage testing and quality assurance in the old days. In the context of big data, cloud, streaming data, and other still-emerging technologies, automated testing and quality assurance is a necessity, not a luxury.
Define big data and data science, learn why the U.S. election result doesn’t indicate inherent problems with analytics, and ensure your enterprise is compliant with big data regulation.
- By Quint Turner
- November 28, 2016
Choose the right cloud model, staff a great data quality team, and ensure that your big data project will create positive ROI.
- By Quint Turner
- November 17, 2016
In their work, many data and business analysts spend the bulk of their time on data preparation tasks using a patchwork of tools. I visited with Manan Goel of Paxata to discuss how to reduce this overhead, how to weave together basic and advanced data preparation capabilities, and how analysts can be more efficient and effective in their work.
- By Jake Dolezal
- November 4, 2016
Data quality on Hadoop is becoming more important as more critical data is being stored there. Consider the automation and performance advantages of an on-Hadoop data quality solution which cleanses data without it ever leaving the cluster
- By Jake Dolezal
- October 3, 2016
The next leap forward in improving information agility is about rethinking who does the preparation work. Self-service data prep increases throughput and allows you to leverage the collective wisdom of the organization.
- By Adam Wilson
- September 29, 2016