Let’s be honest: The phenomenon of Big Data isn’t quite as straightforward as the name it’s been given. The “Big” suggests that it can be reduced to a statement of quantity, but as data analysts know and many companies are discovering, the term actually indicates a set of processes and possibilities that are more complicated and harder to wrangle than simply sifting through an extra-large database.

Big Data refers not just to the volume of data that has newly become available in the digital era, but also the variety, velocity, and veracity of that data (as well as a few other “v” words, depending on your list).

In other words, the data that retailers can now use is as diverse and fast-moving as it is extensive. Companies are pulling information from every conceivable source — from the familiar (e-commerce, social networking, inventory systems) to the more futuristic (RFID sensors, advanced in-store surveillance cameras, smartphone tracking) — and collating all that data with relevant outside metrics, such as weather patterns and other publicly available statistics.

Teaching Data to Talk Business

For those companies that have yet to access their own Big Data potential, devising a program to accomplish this feat is a daunting prospect. They’ll need to put together an IT team to develop a system that integrates all those disparate data sources and generates intelligible (let alone actionable) outputs for decision-makers — no easy task.

Even with many of the existing platforms that are designed to facilitate the transition from slow-moving, labor-intensive data processes to real-time retail analytics based on Big Data (sourced from Point-of-Sale data), those platforms are still built for those who speak the language of statistical analysis, not the language of business.

The pay-offs of bridging the gap are potentially extraordinary, however. With the right program in place, vendors and retailers are able to instantly assess how well their products are selling from region to region and store to store. They can zoom into the shelf level, examine assortments in detail, determine the success of promotions up-to-the-minute, and dramatically revitalize their planning and forecasting.

How to access these benefits without wasting time and resources developing the means to do so? The answer comes from above.

Cloud-based Solutions to Infrastructure Challenges

In order to see how Cloud-based retail analytics solutions can overcome obstacles to Big Data implementation, let’s look at another sticky infrastructure problem: Internet in Africa.

Except for the country of South Africa, the African continent has traditionally had significantly less access to Internet than European, North American and Asian countries. Many factors have contributed to this lack of connectivity, including poor power supply, fewer fixed telephone lines, and scarce bandwidth. Building the necessary infrastructure to overcome these obstacles is slow and expensive.

Rather than wait for traditional infrastructure to catch up to their demand, many Africans have turned to mobile technology. Christine Zhen-Wei Qiang describes this development in a report for the World Bank: “The mobile platform is emerging as the single most powerful way to extend economic opportunities and key services to millions of people.”

“The mobility, ease of use, flexible deployment and relatively low and declining roll-out costs of wireless technologies enable them to reach rural populations with low levels of income and literacy,” she says.

With mobile phone in hand, farmers and other entrepreneurs across Africa are accessing the kind of market information they need — where to buy, when to sell — in order to achieve greater growth and efficiency, as well as creating networks to negotiate more profitably with wholesalers.

Finding the technology that matches the demand

When intransigent infrastructure challenges block access to the benefits of a new technology, sometimes the only way forward is to go right over the problem.

For retailers or product suppliers that need Big Data insights now, the smartest solution might also be the quickest. Cloud-based retail analytics platforms with strong interactive visualizations give decision-makers the information they need to optimize inventory, custom-tailor local assortments, reduce out-of-stocks, and improve supply chains, without waiting for someone to translate the point-of-sale and inventory data for you.

To see how a Cloud-based retail analytics solution can quickly and easily connect your company to the information it needs, try a demo of Askuity’s Retail intelligence platform.