Big data is a collection of data from traditional and digital sources inside and outside your company that represents a source for ongoing discovery and analysis.
Some people like to limit big data to digital inputs like web character and social network interactions; however a lot of people will agree that we can’t exclude traditional data derived from product transaction information, financial records and interaction channels, such as the call center and point-of-sale. All of that is big data, too, even though it may be dwarfed by the volume of digital data that’s now growing at an exponential rate in the world today.
In defining big data, it’s also important to understand the mix of unstructured and multi-structured data that comprises the volume of information.
Unstructured data comes from information that is not organized or easily interpreted by traditional databases or data models, and typically, it’s text-heavy. Metadata, Twitter tweets, and other social media posts are good examples of unstructured data.
Multi-structured data refers to a variety of data formats and types and can be derived from interactions between people and machines, such as web applications or social networks. A great example is web log data, which includes a combination of text and visual images along with structured data like form or transactional information. As digital disruption transforms communication and interaction channels—and as marketers enhance the customer experience across devices, web properties, face-to-face interactions and social platforms—multi-structured data will continue to evolve.
Industry leaders like the global analyst firm Gartner use phrases like “volume” (the amount of data), “velocity” (the speed of information generated and flowing into the enterprise) and “variety” (the kind of data available) to begin to frame the big data discussion. Others have focused on additional V’s, such as big data’s “veracity” and “value.”
One thing is clear: Every enterprise needs to fully understand big data – what it is to them, what it does for them, what it means to them –and the potential of data-driven marketing, starting today. Don’t wait. Waiting will only delay the inevitable and make it even more difficult to unravel the confusion.
Once you start dealing with big data, you’ll learn what you don’t know, and you’ll be inspired to take steps to resolve any problems. Best of all, you can use the insights you gather at each step along the way to start improving your customer engagement strategies; that way, you’ll put big data marketing to work and immediately add more value to both your offline and online interactions.
REASONS WHY YOU SHOULD CARE ABOUT BIG DATA ANALYTICS.
While big data analytics is truly power tool ,its often treated by business as nice to have, but somebody that isn’t totally necessary .This is clear mistake.Keep in mind that if you aren’t using big data analytics to your benefit ,your competitors are using it to their’s.
Given how competitive the economy has become today and that nearly every industry is balking under the weight of more and more competition, you need to leverage big data analytics to your benefit ,and do so wisely. This can lead to you being in the position of making more solid business decision and having the goods to back it up.
Big data analytics help you to answer key questions about your customers, such as who your best customers are ,and what your customers want, and why people choose different brands can also be gleaned from these analytics.
There are only a few of the many advantages and benefits possed by this incredible technology.
Big data is changing the way business is been carried out in today's woreplace and you can't afford to let your competitors leverage on it before you do.
For more information, write to me via my email: isaacgbengs@gmail.com and I will be there to assist you.
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