Earlier this year Gartner predicted that the worldwide Business Intelligence and Analytics market is slated to touch $16.9 billion. Business intelligence & analytics has been undergoing an evolution of sorts.
The business intelligence journey began with decision support systems (DSS) in the late 1960s, but back then computer hardware was expensive and processing power was limited. It was only in the late 1980s and early 1990s that data warehouses, executive information systems, OLAP and business intelligence evolved.
The personal computer became affordable and business people could use office applications such as Microsoft Word, Excel and Access. Business users were thus empowered to develop their own applications and present data visually in the form of graphs and grids.
Excel spreadsheets came in handy for presenting data without assistance from IT. That being said, organizational data was centralized and therefore not directly accessible to end users. Advent of the internet in the 1990s led to a boom in eBusiness and eCommerce applications. Unfortunately, integration with in-house systems was often messy and the enterprise data was either fragmented or inconsistent.
Over the recent years, several big data solutions and tools have been developed to provide businesses with a single version of the truth. Data visualization tools like Tableau, Qlik and Alteryx have become very popular due to the ease with which business users can access insights. These tools cut to the chase by throwing up charts that can be easily understood by them with minimal support from IT.
So, while data visualization tools have paved the way for democratization of data, they have their own limitations –
- No predictive analytics capabilities
- Integration with other apps is not always possible
- Data wrangling capabilities are limited
- Lack of shareable dashboards
- They are not future ready to process data from newer sources
- Limited data visualization options make it difficult to conduct complex analysis
It’s important for BI tools to keep up with rising expectations of the average business user. As users get a hang of these self-service tools, they want to be able to get answers for more difficult questions and discover hidden correlations.
With that in mind we have developed DataScout, a best in class self-service analytics tool that not only cleans messy data, but gives you the freedom to play around and ask questions you always wanted to. DataScout is a true big data application that gives you the full advantage of its natural language processing (NLP) and machine learning algorithms to process structured as well as unstructured data.
It automatically finds the context from your enterprise wide data and presents it in the form of drillable dashboards. It’s point-and-click interface will let you carry out the most complex analysis with ease and share your findings with team members without any hassle. DataScout gives you access to an exhaustive range of data visualization options that lend simplicity to the most complicated datasets.
DataScout is one of the few tools out there which gives its users the opportunity to test the waters through what-if analysis.