Is Your Company a Data Management Leader or Laggard?
November 4, 2016
The article titled Companies are Falling Short in Data Management on IT ProPortal describes the obstacles facing many businesses when it comes to data management optimization. Why does this matter? The article states that big data analytics and the internet of things will combine to form an over $300 billion industry by 2020. Companies that fail to build up their capabilities will lose out—big. The article explains,
More than two thirds of data management leaders believe they have an effective data management strategy. They also believe they are approaching data cleansing and analytics the right way…The [SAS] report also says that approximately 10 per cent of companies it calls ‘laggards’, believe the same thing. The problem is – there are as many ‘laggards’, as there are leaders in the majority of industries, which leads SAS to a conclusion that ‘many companies are falling short in data management’.
In order to avoid this trend, company leaders must identify the obstacles impeding their path. A better focus on staff training and development is only possible after recognizing that a lack of internal skills is one of the most common issues. Additionally, companies must clearly define their data strategy and disseminate the vision among all levels of personnel.
Chelsea Kerwin, November 4, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
The Pros and Cons of Data Silos When It Comes to Data Analysis and Management
February 22, 2016
The article on Informatica Blog titled Data Silos Are the Death of Analytics. Here’s the Fix explores the often overlooked need for a thorough data management vision and strategy at any competitive business. The article is plugging for an eBook guide to data analytics, but it does go into some detail on the early stages of streamlining the data management approach, summarized by the advice to avoid data silos. The article explains,
“It’s vital to pursue a data management architecture that works across any type of data, BI tool, or storage technology. If the move to add Hadoop or NoSQL demands entirely different tools to manage the data, you’re at risk of creating another silo…When you’ve got different tools for your traditional data warehouse versus your cloud setup, and therefore different skill sets to hire for, train for, and maintain, you’re looking at a real mess.”
The suggestions for streamlined processes and analysis certainly make sense, but the article does not defend the reasonable purposes of data silos, such as power, control, and secrecy. Nor do they consider that in some cases a firm is required to create data silos to comply with a government contract. But it is a nice thought: one big collection of data, one comprehensive data strategy. Maybe.
Chelsea Kerwin, February 22, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
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