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The 4 Faces of Big Data Challenges You just Can’t Ignore

Big Data Challenges of FaceBook

Business Decision makers everywhere yearn for the right information that would help them make informed decisions.

30 years back business heads had a challenge of collecting enough data to make informed decisions. Today, the decision makers face challenge of a different kind, one where they have so much data that it is impossible to make sense out of it.

We are talking about Big Data. Big Data is helping organizations of all sizes to make better business decisions, save costs, improve customer service, deliver better user experience, and identify security risks among other things. We read about Big Data everywhere; we listen to it from experts everywhere; even governments are talking about it.

Here we talk about the challenges that organizations face while implementing Big Data.

  1. Ownership
  2. Data
  3. People
  4. Technology

Ownership

Big Data is not a technology initiative, but a business one.

Big Data initiative has to be driven by the leaders of the organization, be it Business Heads or CXOs.

Big Data can help an organization to improve operational predictability, increase sales, improve customer service among other things. These outcomes of the initiative have to be identified and articulated by the Business heads.

Additionally, the procedural and in certain cases structural changes brought in by Big Data have to be managed carefully. Organizations do not change easily and not everyone may appreciate the value brought to the table with advanced analytics. This is a typical organizational challenge that needs to be handled aptly by the top management.

Organizations have to be sure not to label Big Data as an IT driven initiative.

Data

The most important aspect for any organization to benefit from Big Data is the data itself. While there is variety of data collected by various tools and processes, not all data is relevant.

It is critical for an organization to identify relevant sources of information depending on the outcome expected out of the effort.

For example, if you want to improve customer experience on the website, an example of relevant data would be log details about the errors encountered by users while connecting to your website. In this case, you may not want to store or process the log details of successful connections.

Only when there is relevant data, it can be processed and organized in a way that provides meaningful insights to the management to make informed decisions.

People

For any successful Big Data effort there has to be a team of people with the right skills. As I pointed out earlier, Big Data is not a technology initiative, and the skill sets required are not limited to technology.

For a successful Big Data effort, the team should have right mix of,

Data Scientists: Data scientists with their skills and expertise help in deriving right statistics and identifying patterns to correlate variety of data and bring out meaningful insights.

Technology Experts: Technology Experts who bring in specific skill sets to drive the technology that forms the backbone of the Big Data initiative. The team of technology experts will be able to identify the right set of software tools and hardware infrastructure required.

Business Owners: Business owners who can drive the Big Data effort by defining the outcome of the Big Data effort and then working with the technology and data scientist teams to achieve the outcome.

Technology

Technology forms the backbone for any Big Data initiative.

Technology components for Big Data would include,

Hardware Infrastructure: Organizations need to identify their needs and plan for the hardware infrastructure required for their efforts. Cloud Computing is also an option if you are not willing to invest in hardware.

Software tools: You need to invest in the right set of tools for collection, processing and storing of data and for deriving analytics and visualization of data.

Recent advances in Cloud Computing and open source technologies like Hadoop, NoSQL databases etc., have helped in significantly reduce the costs for processing Big Data.

To gain value out of the Big Data initiative and making it a success, it is important for the company to address all of these challenges together. Right set of technology to process the data will not be of any use without people with the right skill sets to derive insights. Leaving out any of these challenges unanswered will not bring out the strategic differentiator for the business.

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