big data vs smart data

Conquering Big Data through Smart Data

Big Data = Volume + Velocity + Veracity + Value

A closer look at this equation reveals why big data is tending to get so unwieldy. It’s got to do with volume and velocity, both of which are transforming big data into a colossus mass of meaningless data, extracting value from which is increasingly proving to be a pyrrhic task. The need of the hour is to transform big data into smart data, so that insightful and actionable information can be mined effortlessly.

What is Smart Data?

It is data which is uniform and regular, and consequently less bewildering. It is the kind of information to which we can apply our personal knowledge and make it instantly actionable. Unlike raw data, that big data typically keeps generating, smart data is something which can be easily presented in compelling visual forms to be understood by all and sundry.

For example: monitoring all transactions carried out for all credit card holders is Big Data, deciphering something meaningful from which can be an impossible task. On the other hand, monitoring the activity of a card number which compares each transaction in near real time with the owner’s purchase history is smart data. The data is small, comprehensible and can be presented visually to easily understand the buying patterns.

So, How Can Organizations Make This Shift to Using Smart Data?

At a very basic level organizations need to rely on having access to VALID and CLEAN data. Next, they need to enhance the data and master its management. This can be achieved through Master data management

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Data management is related to acquiring, maintaining, and making accessible current and correct data. This is a formidable task because it throws up several internal roadblocks such as multiple departments managing the same data sets, or lack of technology and expertise to manage data. Mastering ways to manage data can help organizations increase ROI by marketing efficiently and effectively.

Source Optimization:

This stage involves evaluating the internal and external data sources to determine the relative value of the data generated. Proper evaluation can help to gather and acquire data that is more accurate.

There are a wide range of tools to accomplish this, but the manual work done by data technicians can make all the difference in producing valuable data. This calls for entrusting the task to experienced data technicians who have the skill-sets to understand the overall value of the data.

Data Enhancement

This stage deals with standardizing the data for proper delivery. It entails appending demographic, geographic, psychographic data and other information to streamline interactions to a personal level. This can be particularly helpful in getting strategic insights such as: identifying groups of people with particular interests; opportunities to up-sell and cross-sell; sustain buyer interest and thereby retain profitable customers, improve accurate communications and cut down on wasteful engagements. To make this happen effectively, organizations need to identify the right business objectives.

If the way to conquer big data is through smart data, the way to smart data is through managing CURRENT DATA. Investing in high-end analytics tools can be of little help unless you work with your current data, first. Developing a consistent practice to select and analyze your current data can help you turn your big data into smart data.