5 best practices to free data from silos and boost the bottom line

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Ninety percent of the data that exists today was produced in the last two years; that’s thanks to 2.5 quintillion bytes of data we collectively create every day. That number is increasing rapidly, largely due to new IoT devices, sensors, beacons, and new technologies being created every day.

Data is often seen as someone else’s problem, rather than everybody’s opportunity. This is unsurprising, given the unimaginable scale of information generated by even modestly-sized businesses, and the perceived difficulty of turning this data into usable insight. The problem, however, is not one of data volumes or the complexity of analytical tools, but the lack of integration of different data sources and the technologies that can turn raw information into actionable insight.

If, as Clemenceau observed, war is too important to be left to the generals, then data is much too valuable to be left to the data scientists. If businesses can unshackle their data and make it available to all, they can transform their operations, unlock new revenue opportunities, and build new strategies informed by their vast stores of information.

Here are a few best practices to take into account in the burgeoning Age of Data.

Don’t keep data in silos

Too often various units within a business keep data to themselves. From email lists and net promoter scores (NPS) to ticket close rates, outages, or mobile search data, sharing information can inform operations and strategies across every business department – but only if the raw data can be freed from the strictures of their individual silos, transmuted into a useable, contextualized format, and be viewed in real-time.

Do build “data lakes”

If the problem lies with the lack of integration of different data sources and technologies that can turn raw information into actionable insight, then the solution is to build a single “data lake” that can store all the information generated and gathered by a business. With all your data in one place, a reservoir so to speak, information can be channelled into the various analytics engines, business intelligence platforms, and visualisation tools that turn raw data into usable insights.

Don’t start over on infrastructure

While it might be tempting to knock all your infrastructure down and start over, it’s unlikely that you can close business long enough do build something from the ground up. Instead, take a tiered approach and integrate all your systems into the “lake”.

Do standardize your data sets

It’s imperative to adopt master data management (MDM) practices to create a comprehensive view of data resources, which can manage the complex task of gathering, cleansing, and analyzing the information. This also includes building taxonomies for different data domains and integrating with visualization tools, as well as self-service portals so that individual employees are empowered to access the information they need.

Do contextualize and drive in real-time

If you can’t access data in real-time, you’re not capitalizing on its full potential. If you’re an enterprise-sized organization, making a real-time decision based on data could mean a difference of millions of dollars.

In the information age, data is power. Those who can gather more of it, analyze it more effectively and apply it faster will have a huge advantage over their competitors.

By ending the “siloization” of data, organizations will vastly improve internal collaboration and information sharing between departments and applications. They will more fully understand their own business and operations, be better equipped to exploit new market opportunities, bring new products and services to market much faster, develop a deeper understanding of their key relationships, and uncover correlations that will inform their future strategy.

Moreover, they will be better able to predict demand and implement dynamic pricing, improve operations, identify upsell / cross-sell opportunities, spot customer service or product problems, and harness contextual, behavioral or location data.

Above all, they will turn their internal and external data from a vast, untapped resource, into a source of new revenue opportunities that will repay the technological investment many times over.

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