Achieving Agile Data Prep and Analytics

Today better business intelligence is a competitive differentiator, meaning every organisation must be harnessing the power of advanced analytics. So why do so few businesses realise their analytical aspirations? There are many barriers to valuable analytical insights and chief among them is the difficulty of data provisioning and preparation, which is often a long, arduous process. But it need not be.

Often, when a business user wants to analyse data they must submit a request to their IT department and wait, and wait, and wait… Unfortunately for the IT team this request is just one among many from various lines of business, and each request involves data acquisition and preparation. Each request is treated as a one-off and all can be a lengthy and labour-intensive process for resources who are likely already overburdened with their own projects and deliverables. Through no fault of their own, this creates a request backlog and an inability to meet demands in a timely manner. Frequently, by the time the business user receives their analysis results and asks IT any outstanding questions, that data is no longer relevant, or the original requirement has changed.

For example, a business user requests a report from IT identifying who has signed up for a paid streaming radio service after a one-month free trial, and who has left the service after the free offer. The business user wants to leverage data to target non-subscribers with a special promotion. However, if IT has a backlog because of other pending requests, the business user may not receive the results until weeks later. This directly affects revenue. The business user could have converted some non-subscribers with the special promotion had they received the data in a timely manner. But a delayed offer due to lack of timely data means the non-subscriber lost their interest in the streaming services and has moved on to something else. By the time the data is available, the special offer is not worth distributing because potential customers have left the platform for a better deal from a competitor.

How businesses approach data prep and analytics can make or break a business in the digital age. Organisations streamlining and automating the data prep process and putting high-quality data for advanced analytics at business users’ fingertips have a significant competitive advantage.

Agile Data Prep Tools and Techniques

Advanced and agile data prep technologies and approaches can eliminate time-consuming, manual data prep procedures and give business users greater transparency and flexibility to enable advanced analytics in real time – delivering better insights and business results. The best of modern data prep and analytics tools enable self-service and democratise data across your enterprise, encouraging business users to use analytics for better business insights.

To empower your business users and truly democratise data and analytics, you need tools that promote self-service, transparency, and collaboration. First, you want a tool that enables users to easily access virtually any data source, and easily acquire and parse the data in a fraction of the time. Giving users access and reusable functionality to visually collaborate as they analyse data from disparate sources creates better understanding of risks and opportunities for the business.

Too often, users are saddled with the constraints of Excel and Access, lacking scalability, repeatability, and clarity. They can be labour-intensive, hard to maintain, prone to human error, and often quite frustrating. Other analytic processes can be “black boxes,” in that they produce results, but you have no way of identifying how those results were generated. So, if you have two reports with contrary results, it’s difficult tracing the source of the data to know which report is accurate.

What you need is a tool that gives you transparency into every step of the process and automates data blending and cleansing to allow business users to profile, aggregate, correlate, and transform selected data. Ideally, this process will feature collaborative feedback loops between IT and business users to promote cooperation, fast communication, and ensure that any changes don’t derail the entire analysis process.

In addition, self-service analytics should put the power of advanced analytics in the hands of business users and provide a unified tool set for preparing data, creating models, and embedding those predictive analytics within any business process. By incorporating pre-packaged sets of popular statistical and predictive routines, it can eliminate the need for programming, and drastically reduce time to insights.

Finally, a complete agile data preparation solution should integrate easily to other data management systems in the enterprise, allowing consumers of data to understand the source and context. Additionally, this allows governance and lineage systems and data stewards to track and report on transformations and data consumption within the business.

With a modern solution suite and a new approach to agile data prep, businesses can uncover insights that were impossible to find using outdated approaches.

Impactful Analytical Insights

With an agile data prep process, business users can now uncover analytical insights that previously would have gone undiscovered or misreported. A good example comes from the cable industry. A cable company was using Excel spreadsheets to track subscriptions and churn. When a customer would cancel their service, the finance team would manually search the active subscriber sheet for the subscriber, count them as churn, and move them to another sheet for possible recovery. However, there were many discrepancies and vlookup errors with numerous duplicates on both spreadsheets.

When they employed an agile data prep tool, the company quickly determined they were significantly under reporting customer churn. For instance, when a subscriber with two services cancelled, the vlookup only matched the first service causing inaccurate calculation of the churn impact. Eliminating these improved the customer experience by eliminating erroneous communications and more accurately reflected business performance in reporting to the board and public markets.

Simple examples like this illustrate how data analysis can significantly impact an organisation’s revenue and efficiency. An agile approach to data prep and analytics can empower your business users, encouraging collaboration between IT and business, and provide greater transparency and understanding into analytic processes. Organisations that empower business users by giving them access and analytic capabilities drive greater understanding of data’s value and help use analytics to uncover additional insights to gain a competitive advantage.