Are You Leveraging The Power of Data Analytics Yet?


Data Analytics is the science of examining, concluding and implementing the useful data for organization’s growth. In today’s connected world, data is available everywhere.  Travis Oliphant, CEO of data analytics firm Continuum Analytics, suggests data is more available now than ever, with “people connecting through the Internet, their mobiles, social media, business partnerships and personal friendships and associations.”

Globally, 4.6 billion mobile subscriptions and around 1 to 2 billion people are accessing the Internet on a daily basis; therefore, the potential for data collection is enormous.

The structured and unstructured data are enormously available, but they are seldom used by organizations to be benefitted in annual growth. The big data is continuously used by technology industry for strategizing annual goal.

Why is Data Analysis Useful to Your Business?

“Something is always better than nothing.” – To weave a strategy for growth of the business, the data availability is always a basic requirement. The voluminous data give the clear structure to carve-out the plan to cover the deficient areas in the business. Data Analysis can help give you not only an insight into your customer’s habits, preferences, and behaviors but can also be applied to help your business grow. For example, if launching a new product, analysis of current customer behaviors can help identify a need for your product, potential future customers, how to market to these customers and how to retain these customers.

Already well established, with over 89% of US businesses saying they use data analytics, data analysis has been adopted by many industries across the globe including:

  • National Governments – In 2012, US Government announced the Big Data Research and development initiative to examine specific issues within government. At present, there are 84 programs.
  • Healthcare Sector – In the UK, data analysis of prescription drugs showed a significant discrepancy in the release of new drugs and the nationwide adoption of these treatments.
  • Elections – In India, the BJP winning campaign for the General elections in 2014, relied heavily on big data analysis.
  • Media – Relies completely on big data to fetch precise information, specifically where figures play a significant role. Media dominates the market by presenting the data as a secure and inevitable witness.
  • Science – Science and technology are correlated and share especial configuration. The huge amounts of data produced during experiments such as the Large Hadron Collider are analyzed using data analysis. The systematic data analysis cut shorts the risks engrossed.
  • Sports – Sports sensors are used to assess athletes and sportsmen’s condition, guide training and even predict injury. The sports related data analytics is required to be precise.

Collecting data is not the issue, in their video, Big data what’s your plan?  McKinsey suggests that companies struggle with data analysis in three key areas:

  1. Which data to use and where to source it?
  2. Analysis of the data, plus sourcing the right technology and people to carry out that analysis,
  3. Implementation of the analysis findings to change your business.

So let’s start with number one…

Lingering around the start line- Deciding on what, when and how to use the Big Data?

Data is now more accessible than ever. To improve the efficiency and other services, every organization collects the related information; however, very few analyze this data to implement in the direction of improvement or change.

Data trends can highlight success, identify problems and help provide alternative ways of working.  And while most businesses know that data analysis can make them more efficient, productive and even help predict future market trends, it is scarcely used to its full potential. So why aren’t more people using data analysis?

The Big Difficulties of Big Data Analysis

Due to the large volume of structured and unstructured data, it often becomes difficult to manage and procure the relevant information from them. On the other hand, the traditional data analysis, which constitutes difficult methods become too wary to analyze. Traditionally, companies use to visualize datasets in programs such as Microsoft Excel which has a great capacity for simple datasets or employ a free tool such as Qlikview, but with Big Data things change.

With over $15 billion spent solely on companies focusing on data management and analysis, companies are forced to employ data analyst or data scientist specifically for data analytics. In 2010, the industry was estimated to worth more than $100 billion and predicted to grow at approximately 10 % a year. So big data is big business.

Analysis of data and implementation of findings is what matters

To apply data analytics to your business first you need a plan or strategy. For example, if you want to improve your company’s effectiveness and efficiency, it is important to manage performance. To manage performance, you need to measure it. But the measures of performance you take need to be meaningful, and link to the desired outcome or goal.

Therefore, the idea to employ a data analyst and specific software, to collate data and develop a plan of how to implement the required changes is quite synchronized.

Ready to trap the Big Data?

Using Data analytics provides potent information which can be used to achieve high merits of success and tangible solutions with great accuracy. It is not only great for your business, but data analysis can also identify customer preferences and behaviors, allowing you to personalize your products and business to your customers.

In today’s connected world, data analytics is becoming vital for businesses who want to gain a competitive edge over others. And with the increasing amount of data available, never before have you had so much access to what your target market wants and needs.

So get out there and see how data analysis can change and improve your business, you might just be wonder why you haven’t exploited data analytics potential before.