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Benefits of data blending: more sources for smarter decisions

Data is the fuel that drives the world around us. Whether it’s a consumer using a FitBit or a business user looking to analyse performance, it all comes back to data. In fact, IDC’s Digital Universe study predicts the amount of data on the planet will grow tenfold by 2020 – from around 4.4 zettabytes to 44 zettabytes.

But harnessing it for analysis has been a major hurdle for businesses everywhere.

Traditionally, IT departments have managed data for their businesses in a centralised manner – and that came from only a few applications. Now, BI is a completely different ballgame. IT doesn’t truly own the data any more. Instead, business users today are the “data owners.” In other words, the data is generated, managed and/or accessed exclusively through line-of-business applications or services – never flowing through a central IT department. In fact, the IT team might not even know about it.

Complicating matters further is the fact that companies are not just collecting ever-increasing volumes. They’re also collecting that data from a dizzying number of sources – applications, sensors, machines, and more – and in multiple formats.

It’s important for organisations to realise that data is no longer centrally located, and continuing to operate on a strictly IT-centric model is unrealistic. Tech-savvy users are clamoring to get their hands on all this data from their core applications so they can make more informed business decisions.

Companies can no longer flow all their data through a master system, store it in a warehouse, and call it a day. Today, we face the complex task of tracing its origins, blending it, and getting it into the hands of users for analysis – all at the speed of business.

Following the flow

exchange of everything

The landscape of where data originates is vastly different than it was a decade ago. As previously mentioned, data ownership has shifted from IT to business users. Today, individual departments manage their own applications and generate their own data. And everyone in the organisation has to not only figure out how to access that information, but also decide what to do with it.

On top of that, some of this data isn’t “owned” by any single department. For instance, think about data from social platforms like Twitter and Facebook – or, in the case of manufacturing companies, data that comes from machines and sensors.

Some companies also use public data – in other words, those they’re not even generating themselves. For example, weather data is useful to logistics or manufacturing companies, while census or demographic-based one is useful in the retail sector. These are all new classes that can be very valuable – but only if you have a plan for combining the sources, storing them, and building analytics on top.

Combining data

Today, we call it “data blending,” and it’s a much more sophisticated process. Not only do we display the data, we join (or combine) it to find common values, and then we query it to gain insights.
One may think that this is the exclusive domain of IT teams, but the practice is something that data-savvy business users want to be able to on their own – without having to wait for the IT team.

The idea of a central data warehouse where you store blended data is just too difficult to manage. Data today is updated constantly, and different people will want to combine it in different ways. For instance, your marketing team may want to blend its Marketo data with Salesforce, as well as data from Unbounce or Google Analytics. This will be vastly different from the finance team, who will want to blend data from Salesforce with Quickbooks and some internal data.

The key is to get these capabilities into the hands of your users. BI technology has evolved to simplify its preparation. Self-service data prep tools can enable the everyday user to connect, acquire, and blend data from nearly any type of source; cache it in a high-performance, self-tuning repository; and prepare it using smart profiling, joining, and intuitive data enrichment. Business users don’t have the skills, or time, to rely on complex data extraction or ETL processes to get some meaningful insights.

When users are empowered with all their data and don’t have to constantly request access from IT, they’re able to do more sophisticated analysis and make smarter decisions, because they see a complete picture – not just pieces that they have to mash together in Excel.

The role of app developers in data access

When you look at consumer applications like Amazon, Netflix, and Facebook, they are all centered on data. You might not think of them as analytic applications that serve up a wealth of data to inform decisions, because they’re wrapped up in slick user experiences. But in fact, they provide analytic information to users where they need it most.

While people want the ability to combine data from various apps, they also want the ability to quickly analyse it to make quick decisions. Users want to be served up information where they need it, at the moment they need it – and they want it to all be easy to use, so they don’t have to think about being trained up on analytics.

This means embedding analytics deep within the app experience, so users can actually be informed about the business and take action based on that information all within the same context. It means creating a better user experience so your users can become much more efficient in the way they work every day.

Rethinking data management

The advent of new and disparate data sources means we must rethink the way we manage data. We cannot simply modernise the traditional model of a centralised system. Instead, we must focus on a higher degree of self-service – empowering our users to make better decisions around the data wherever they sit in the organisation.

This means both empowering users with analytics embedded within the applications they use every day, we well as offering self-service data preparation tools that enable business users to connect, acquire, and blend their data for analysis.

The demands from users are only going to get louder, so organisations should consider how to address data management and data access sooner rather than later.

Image Credit: Maksim Kabakou/Shutterstock

David Abramson, Director, Product Management, Logi Analytics