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 . . . → 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. While the odds for picking a prefect . . . → Read More: Big Data: Three Ways to Choose Meaningful Analytics
The big data Hadoop hype is running into reality, and some companies are not liking Hadoop’s options and features. Following are some of the Hadoop facts that a friend of mine noted to explain why their company was migrating their big data project from Hadoop and into the DB2 z/OS environment.
Hadoop is not free. . . . → Read More: Why Hadoop Is Not the Big Data Solution
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
After implementing a big database with billions of rows, it’s time to run your applications and reports. Hopefully, the database is partitioned so the applications can utilize parallelism and complete your application and reports quickly. When you begin to write your SQL against these tables, take into consideration the first set of DB2 . . . → Read More: 5 Big Data SQL Performance Tips — Fixing Generated SQL
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
The race is on among all the vendors to lock your new Big Data project in to their architecture, platform, and support contracts. All the open source Hadoop derivatives have boiled down to the leaders of Cloudera Impala, Teradata SQL-H, EMC Pivotal (formerly GreenPlum) MongoDB, and one of best–IBM’s BigSQL.
All of these vendor’s solutions . . . → Read More: 5 Reasons Why DB2 Is Still the Best Big Data Solution
Big Data disaster recovery is a big issue. Of course, any Big Data business sponsor vows that the entire Big Data database is necessary, and demands it be included in the disaster recovery plans. This requirement makes getting a Big Data disaster recovery sync point and understanding the intimate Big Data processing transaction details to . . . → Read More: Big Data Disaster Recovery: 4 Reasons Why DB2 Cloning is Excellent
During the Big Data DAMA-NCR Meeting in Washington D.C. this week, I heard from Svetlana Sicular, Research Director of Data Management Strategies at Gartner Group; Raul F. Chong, Senior Big Data and Cloud Program Manager at IBM; and John Adler and Madina Kassengaliyeva from Think Big Analytics.
Their insights into Big Data projects were quite . . . → Read More: Big Data Day Recap — 5 Very Interesting Items
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 . . . → Read More: Big Data: Leverage the New Fantasy Football Data Model?