In a world of information overload, analytics professionals have to focus on delivering consumable analytics. Visualizations and alert systems allow users to more easily consume and use data.
- By Troy Hiltbrand
- October 4, 2016
Machine learning is a hot topic today and businesses around the world are using it to gain a competitive advantage. It is not a magical technology, rather the application of time-tested statistical practices to common business processes.
- By Troy Hiltbrand
- September 16, 2016
Amazon's Aurora may close the gap between spreadsheets and full-blown RDBMSs for large enterprises.
- By Troy Hiltbrand
- July 22, 2016
Organizational needs are changing, and data professionals are rethinking what they really need from an analytics database. With a whole new group of leading NoSQL databases, there are alternatives for storing and managing data.
- By Troy Hiltbrand
- July 19, 2016
With the popularity of data science, schools around the world are training students in the necessary technical capabilities. In addition to these skills, future data scientists need certain personality traits to be successful.
- By Troy Hiltbrand
- June 13, 2016
Finding common attributes to join customer data across multiple data sources is extremely important, but it can be time consuming and challenging. Thankfully, there are methods and tools that can help in this process.
- By Troy Hiltbrand
- June 6, 2016
Effective data preparation depends on recognizing how to handle what we know and what we don't know about a set of data. Our goal as analytics professionals is to make less unknown and more known.
- By Troy Hiltbrand
- May 17, 2016
Filling the gaps in data can mean the difference between an analytics project's success and failure. Choosing the right method is a combination of art and science that requires understanding the business, the data, and the targeted decision.
- By Troy Hiltbrand
- May 9, 2016