What is Assisted Predictive Modeling?
Assistive Predictive Modeling incorporates complex, sophisticated analytical and forecasting techniques in a self-serve environment where business users can employ tools to guide them through recommended techniques and report formats and ensure that the methods and reports they choose are appropriate to the type of data and information they need.
Sometimes we are so focused on perfection that we do not see the benefit of agility. Consider the emergence of the brainstorming concept as an example. We learned quite some time ago that if used the brainstorming concept of freewheeling, non-judgmental discussion we could bounce ideas off one another and often come up with innovative ideas that would not have resulted from a discussion that was more restrictive.
SSDP (otherwise known as self-serve data preparation) is the logical evolution of business intelligence analytical tools. With self-serve tools, data discovery and analytics tools are accessible to team members and business users across the enterprise.
Data prep can slow down analytics and cause delays. Self-service data preparation (when done right) can enable business users to leverage sophisticated, easy-to-use tools for self-serve ETL. Data extraction, transformation and loading (otherwise known as ETL) can be time-consuming and requires professional skills but self-service ETL will walk business users through an augmented data preparation process and take the complicated, confusing steps out of the process by helping the user make decisions on how to prepare, clean, reduce and use the data in the best way possible.
In years past, data preparation was the domain of IT professionals and data scientists. In order to prepare data for analysis, one had to find, gather, and prepare the data and that preparation included cleaning, combining, reduction and shaping of the data.
Self-Serve Data Preparation is a critical component of augmented analytics. If these terms seem foreign to you, just know that they represent the future of business analysis. As organizations adopt self-serve business analysis, the business user with average technology skills must be able to leverage tools that are sophisticated, yet easy to use.
Self-serve has many meanings. You can pump your own gas, you can serve yourself at a buffet, and sometimes you can even do your own data preparation. You will notice that I said ‘sometimes’. That is because you have to choose the right tool if you want to really participate in self-serve data preparation.
Self-Serve Data Preparation (aka augmented data preparation) is all about efficiency and the presentation of sophisticated data preparation tools in an easy-to-use environment. The idea behind self-service data preparation is to give the average business user the ability to prepare, use, report on and share data without the assistance of IT staff or analysts, thereby making their jobs easier and making every team member more of an asset to the organization.
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.
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.
