On January 13th IBM unveiled its new mainframe, the z/13. IBM mainframe System z’s world-leading reliability, availability, and scalability, coupled with its security and virtualization capabilities are needed more than ever as mobile applications take over as the most prominent and important corporate workload. Today’s corporations are embracing mobile workloads that grow at a much . . . → Read More: z/13 IBM’s New Mainframe Built for the Mobile, Cloud and Analytic Future
While I have talked a lot about big data through this blog it is really important to remember that our, phones, iPads, Fitbits, and all computers are listening devices. Now even your car’s navigational equipment and black box can tell the latest details of your driving skills—good and bad.
So below are three things that . . . → Read More: Big Data: Three Big Brother Reminders
The last two weeks I have talked about ways to choose meaningful business analytics and then fine tune the focus of your business analytics. This week I talk about the factors needed to further fine tune your analytics into effective results for your company. Some of the ideas might even help you get . . . → Read More: Big Data: Four Factors to Tune your Meaningful Analytics
Last week I talked about ways to choose meaningful analytics. Here are three more ways to make the analytics even better for your big data project.
Focus the analytics only on a specific business aspect. Last week I stressed analytical focus on the money aspects. This week we need to take that focus one . . . → Read More: Big Data: Three More Ways to Choose Meaningful Analytics
The NCAA tournament is going to start in a few weeks, and everyone is going to get their basketball winning prediction bracket ready. Quicken Loans, insured by Warren Buffet, is offering $1 billion dollar prize for anyone picking a prefect bracket for the NCAA tournament. . . . → Read More: Big Data: Three Ways to Choose Meaningful Analytics
Today’s big data provides more analysis opportunities and puts greater pressure on every company’s business model to produce profits. Now big data analysis can be applied and used to optimize any and all phases of your company’s business model.
Customer sentiment, website clickstreams, sensor data, geo location data, all operations logs, and any structured or . . . → Read More: Three Ways to Pursue the Correct Big Data Project
Everyone is talking about implementing analytics within their company or department and using the power of big data to gain a competitive advantage. Previously, I talked about how to get your analytics efforts going in this blog post (http://davebeulke.com/big-data-five-ways-to-get-analytics-started/). The truth is getting an analytics reporting process into everyday business activities is a difficult task. . . . → Read More: 5 Big Data Analytics Success Factors
Big Data analytics are all in fashion these days, but there are many issues with how analytics are used, and how developing the appropriate analytics takes a correct and thorough data model. As I talked about in my previous Big Lies, Big Damn Lies and Statistics blog post, there are many different ways analytics . . . → Read More: Big Data: Leverage the New Fantasy Football Data Model?
The last two weeks I talked about evaluating reporting tools, the different tools criteria categories, and determining the particular important sub topics that are unique to your company. This week we are going to talk about the Big Data itself, and four ways to determine the best areas to cover in your analytical research for . . . → Read More: Big Data: Four Ways to Identify Domains Areas for Analysis
The following are the remaining five criteria for your Big Data analytics reporting tool. As I mentioned last week, weightings for each criteria category should be discussed, along with adding your company’s sub-topic considerations, to calculate the total best score. By using these criteria and attributes as a starting point your company can quickly understand . . . → Read More: Big Data: Ten Criteria for Evaluating Analytics Reporting Tools (Part 2)