There is no facet of modern human existence that is untouched by technological innovation. As dwellers of the information age, we are at the juncture in human history where we expect inanimate objects to fit within our busy lives. ‘Cellular phones’ and ‘mobile phones’ are fast disappearing from our vocabulary and replaced by smartphones.
We are now a smartphone generation surrounded by smart fitness trackers and home appliances. Like everything in our life, it’s only natural for us to expect the same level of technological intuitiveness in the way we work. From the factory floor to the office, we’ve achieved many technological milestones and now we are the tipping point of technology that drives business intelligence.
Although there has been a lot of talk about Big Data over the years, it’s only recently that businesses have started realizing the benefits of big data analytics. Monetization of big data analytics hasn’t been without evolutionary changes.
Business leaders today need to make informed decisions and they need to make them fast. Gut decisions unsupported by factual insights is a fast disappearing practice. Business intelligence required by decision makers were once an exclusive purview of IT specialists.
The traditional approach to business intelligence was a middlemen affair played out by IT specialists. Business users were asked what they wanted. Designing, developing, testing and maintaining reports would then become IT’s responsibility, thereby confining business users to a predefined set of reports. Anything outside that would be a special request that would take weeks and months.
Improvements in the traditional approach started happening in the form of limited self-service capabilities where users could drill down a few levels deeper, change data visualization from pie to bar or line chart and apply some basic filters. Adding new sources of data to strengthen decision making would still be treated as a time and resource intensive, special request.
Self-service analytics tools like QlikView, Tableau and Spotfire have now freed business users from the shackles of IT dependency. Their intuitive and easy to use interface empower every user in the command chain to prepare their own reports and consume them in any way they want. These data discovery tools have made IT skills redundant.
The most defining aspect of self-service analytics is the ability to get actionable insights when they are required. It’s no wonder that the above-mentioned tools have achieved phenomenal growth in a relatively short amount of time. Enterprises have readily embraced self-service technology and the role of IT specialists has been transformed into facilitators.
Self-service technology is a boon for IT as it has been struggling to keep up with a barrage of requests and ending up with backlogs. Technology has accelerated business performance, which means that the frequency with which business users consume analytical reports has increased. Data visualization tools have successfully removed the analytics bottleneck.
However, if business users want to additional data from social media sites or spreadsheets from market research companies they need IT support for that. Such requests can again take a long amount of time.
To eliminate such IT dependency issues tools like Tableau, Alteryx and Qlik have data wrangling capabilities. With minimum or no IT support users can integrate data obtained from a social media network or private spreadsheets. Since this makes data available to everyone and not just IT specialists, a great level of data democratization is achieved.
There’s a catch though, business users can use data wrangling features by applying their own logic to integrate data from different sources. While IT specialists understand data structures, they don’t understand the data itself. Business users on the other hand have the contextual understanding of data, but don’t understand data structures, this restricts them from getting the best out of their business data.
In this whole evolution of data analytics tools, business users need a tool that not only integrates data but prepares it too. We’ve therefore created, DataScout – a highly evolved on-demand analytics tool.
DataScout is fitted with a range of machine learning algorithms that automatically integrates data in the best way possible and shows unfathomed correlations. It’s how business users can truly harness the beauty of big data analytics and eliminate dependency on IT.
DataScout not only integrates data, but it’s smart about it. It understands the business user’s need for better contextualization of insights. It gets better every time you use it to give you the decisive insights you need to steal a march over the competition. It will point you to the money-making decisions you need to stay ahead always.
We would love to show you how DataScout can assist you in making real-time decisions.