Self-Serve Data Preparation is the next generation of business analytics and business intelligence. Self-serve data preparation makes advanced data discovery accessible to team members and business users no matter their skills or technical knowledge.
There is too much to do in a day to wait for someone else to give you the data you need. But, when it comes to data preparation and data analytics, business users are usually not comfortable with complex solutions that are time consuming or that require professional analytical skills. You pay your team members to have a certain type of expertise and that doesn’t always include technology or analytical knowledge. So, if you want them to be a real asset to the organization, you have to give them easy-to-use self-serve data preparation tools. Self Serve data prep allows business users to quickly gather and prepare data for analysis and to answer questions and solve problems without delay.
Every enterprise is talking about Business Intelligence and Advanced Analytics. Every enterprise has considered the benefits of implementing self-serve analytics across the organization and involving business users in the process. Panel discussions at technology conferences and hallway conversations among executives and IT staff encourage the trend and create anxiety within the organization that has not yet embraced advanced analytics at the grassroots level.
What is self-serve data preparation? It isn’t a method of making up data. It is a method of preparing data that allows the average business user to compile and analyze data without the assistance of a data scientist or an IT professional.
By providing sophisticated analytical features and algorithms in an easy-to-use self-serve environment, the enterprise enables business users to perform data preparation and test theories and hypotheses and prototype on their own. Rather than preparing data at the central meta-data layer, and restricting what business users can do and see, IT enabled (rather than IT controlled), self-serve data preparation allows users to compile and prepare data and use that data in analytics to test hypotheses, perform visualization and create and share reports, and create custom alerts and other information. Business users can control the data elements, the volume and the timing.
To be successful in business, every organization must find a way to accurately forecast and predict the future of its market, and its internal operations, and better understand the buying behavior of its customers and prospects. With the democratization of business intelligence and the advent of self-serve business intelligence tools, organizations hope to encourage and create Citizen Data Scientists and enable the average business user to leverage sophisticated predictive algorithms and BI tools without the expertise and skill of a trained data scientist. This approach allows users who are not statisticians, data scientists, programmers or analysts to leverage self-service tools to confidently make business decisions, share data, and reports and present data in a way that allows the organization to identify trends, patterns, opportunities and challenges.
This might be a strange comparison but let me make it anyway! Think of data agility and data quality like a tight rope act. The tightrope walker is thinking about getting to the other side without falling. The audience wants to see grace and beauty during the process. They want to see a QUALITY act. In the case of the tightrope walker and the audience, they sometimes have very different goals.
I vote for Data Democracy. Why? Because data belongs to everyone in your organization and if you can find a way to provide data democratization, and provide your business users with mobile BI tools, self-serve business intelligence, social BI tools and self-service data prep, your organization WILL reap the benefits.
