Considerations to Make Before Investing in Big Data in 2013

Industry Week recently published <>  a viewpoint I wrote entitled ‘Five things to consider before you make big data investments in 2013’. Due to the massive volumes of valuable unstructured data permeating the average organization on a daily basis, innovative IT executives are moving fast to leverage this untapped data for more meaningful business insights and enhanced decision-making capabilities. We know big data can deliver unprecedented insights into business. Both IDC and Gartner expect big data spending to accelerate in 2013 and beyond.   

Five Things to Consider 

The article identifies the following five things to consider when making big data investments and discusses each in greater detail.

  1. Big data will create new opportunities to understand and manage things differently because it promises to bring disruptive change across all industry segments and give the companies an unfair advantage.
  2. The synthesis of social media and in-house data creates a compelling picture.
  3. You don’t have to start with big data – in fact master data management is a good place to start to ensure you are working with clean data that is semantically coherent.
  4. The cloud will play an important role by allowing you to focus on the solution, not the purchase of specific technology such as SAP Hana or Hadoop.
  5. Data scientists are critical to the success of big data and hence are a precious resource.

The article goes on to give several examples of multiple big data initiatives, such as incorporating social media to get 360 degree customer feedback, improving competitive intelligence or identifying fraudulent activity such as grey market for your products, or false product returns against your product warranties.  


Further Reading


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Pete Ianace says:

Where is the real value in Big Data?
Taking a look at the Big Data frenzy one should ask the question, how much of Big Data is actually useful. By applying just a little common sense we discover only a small amount.
I have been working with data for over 40 years and if we go back to pre-internet days we experienced what we called data overload and we discovered then that data itself wasn’t valuable but only a small slice of that data proved to have a direct impact on actual business decisions. With history in mind what has really changed in solving the most critical issue in related to finding the data that is actually useful. Well volume has certainly increased, but what is important to deal with is that much of the growth in volume comes in the form of unstructured data. So let me start with what is unstructured data using the definition from Webopedia.
Data can be designated as unstructured or structured data for classification within an organization. The term unstructured data refers to any data that has no identifiable structure. For example, images, videos, email, documents and text are all considered to be unstructured data within a dataset.
While each individual document may contain its own specific structure or formatting that based on the software program used to create the data, unstructured data may also be considered “loosely structured data” because the data sources do have a structure but all data within a dataset will not contain the same structure.
This is in contrast to a database, for example, which is a common example of “structured” data.
So looking back in history we are talking about data overload with an added new twist called unstructured data, which represents much of the new volume being generated. I would suggest that companies that bring a combination of strong data analytical expertise along with a good grasp of both industry standards and compliance rules can make offer precise filtering solutions that can identify the most valuable data for the user..

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