The Evolution of Big Data and Tackling the Cost of Bad Data

- 11th Jan 2017


Having poor quality data is one of the biggest challenges enterprises face today. How can businesses strategically leverage customer data in their marketing strategies  and campaigns? As enterprises are putting more investment in managing and maintaining big data, numbers need to be reliable and accurate.

In our last blog, we discussed the role a Customer Relationship Management (CRM) platform plays in nurturing an enterprise’s relationship with its customers. Here, we go deeper to explore the core of CRM and understand the Big Data that it houses.

The Evolution of Big Data

Today, data is no longer confined to the realms of a tech company, with insurmountable data being churned out every day in all industries. Data is contributing significantly to brand equity and is setting a benchmark for quality product and service delivery in a highly competitive and connected global market. Companies across all industries are increasingly becoming data-centric and data-driven to score a competitive edge.

However, too much is changing too fast and data is growing at an exponential rate.

In 2015, Forbes reported, “more data has been created in the past two years than in the entire history of the human race.”  This fact is only the start of what we’ve been seeing in online research. By 2020, a staggering 4.4 zettabytes of accumulated digital data is set to take a big leap to 44 zettabytes or 44 trillion gigabytes.

Enterprises cannot afford to ignore the magnitude of this forecast. The startling revelations give Big data an appalling aura, making it appear larger than life, yet it has an intriguing element to it. Revelations, in particular like, “retailers who leverage the full power of big data could increase their operating margins by as much as 60%,”  invariably holds a lot of promise for the retail sector.  On the other hand, less than 0.5% of all this data is presently put to use. There is a floodgate of opportunities for the sector.

Internet of Things and Big Data

So what is causing this data furor? Almost everything, from the digital world and physical world adds to the pool of big data. We are constantly chatting, emailing, sharing, purchasing, uploading, downloading, tweeting, following, streaming, conferencing, working online and doing so many other things. The advent of Internet of Things (IOT) inevitably brings significant changes to Big data.

IOT takes the concept of connectivity and communication beyond the realms of human diktat into an era of hyper-connectivity. It makes any sensor-enabled device, machine or appliance interact and communicate. Consequently, it combines streaming data with robust analytics to make realistic forecasts and quantitatively enhanced real-time decision making. This giant network of connected things and seamless communication between people-people, things-things, and people-things is creating both possibilities and challenges simultaneously.

Continuous streaming of digital data by IOT makes Big data appear increasingly overwhelming to manage and process, because data from connected devices may not be relevant. Even moreso, it can be challenging to separate the poor-quality data to assure quality, usability and value of the data enterprises are investing in.

Tackling Poor Quality Data

Enterprises are looking for authenticity and accuracy in the large data gathered across channels. The Big data pool invariably contains all kinds of data, from good and bad to being useful and unusable. Poor-quality data is one of the biggest challenges enterprises face today, because it hinders an enterprises’ ability to optimize performance and make sound decisions, all the while costing the company a significant investment. Gartner surveyed that the cost of poor quality data is a staggering $14.2 million annually.

If you expect big data to deliver on its quintessential business value proposition, refining and improving the quality and usability of data should be your priority. Enterprises need to understand that any decision making based on poor quality data will have inefficient results.

Leveraging accurate and useful data will allow enterprises to identity problems rapidly, instead of wasting time analyzing invaluable numbers.

Give Your Data the Proximity Edge

Location-based services and technology for enterprises might be the solution you are looking for if your goal is to leverage accurate and valuable customer data. Proximity MX, a location-based marketing solution, through its accurate, reliable and real-time data powers you with unique contextual intelligence that you can trust for your crucial marketing decisions.

Top retailers are using big data to gain a competitive advantage by predicting trends and preparing for future demands. The data when powered with a Proximity platform leverages real-time analytics big time and in turn, can help retailers make decisions on a granular level.  Retailers can segment customers by expected buying behavior and reach them as per their preferences, when they are in the right location and engage them with personalized real-time offers.

There is definitely a lot happening over big data, and just like other sectors, retail can immensely capitalize on the untapped potential it offers. Power your big data with Proximity MX if you’re looking for quality customer data. Click below to request a demo.