There are a myriad of predictive analytics techniques and predictive modeling algorithms and you can’t expect your business users to understand and use them. If you are taking on an advanced analytics initiative and you want to leverage data democratization to cascade data analytics and data literacy throughout the organization, you will need a data modeling solution that takes the guesswork out of the process.
Some people hear the term ‘assisted predictive modeling’ and their eyes cross. They immediately presume that we are talking about something complex and certainly NOT for them. Nothing could be further from the truth. This seemingly complex term actually describes a technique that is designed to be suitable for business users with average technical skills and, with these tools, the average user can enter the age of advanced analytics and make educated, confident business decisions about forecasts and predicted results.
Plug & Play Predictive Analytics is not an exotic process that is limited to data scientists or IT staff. Plug & play predictive analysis is so named because it really is a plug and play process. This type of predictive analytics tool is designed to be accessible and usable by business users.
Assistive Predictive Modeling allows business users to leverage a self-serve advanced analytical tool and to enjoy complex, sophisticated forecasting and business predictions in a simple, user-friendly dashboard environment – all without the skills of an analyst, data scientist or IT professional.
Assisted predictive modeling is no longer the sole domain of data scientists and IT staff. With the right predictive analytics tools, your business users can accurately plan and forecast results and share data to build a dependable picture of the future for your organization, and for each team, division and individual.
Does your business intelligence solution provide true advanced analytics capabilities? Can your BI tool satisfy the needs of business users, data scientists and IT staff? That may seem like a tall order but with the right business intelligence software, you can provide predictive analytics for business users, including assisted predictive modeling that walks users through the analytical process and allows them to achieve the best results without a sophisticated knowledge of data analytical techniques.
Anything that can help your business users to understand, interpret and analyze data is a help! Users have many tasks to perform in a given day and while analysis may not be their forte, they definitely need clear, concise data to share, to make decisions and to see opportunities, challenges and patterns.
Oh, the confusion of advanced analytical terminology. Read a report, attend a conference and your head is swirling with terms like ‘assisted predictive modeling’, plug n’ play predictive analysis, smart visualization, augmented data discovery and augmented data preparation. Add to that, the sophisticated concepts of auto-suggest, auto-recommend, time series forecasting, causation and prediction and classification techniques and you may feel that you need a degree in data science to do your job.
This is a small note on small data. I hope it has a big impact. The common understanding of the world is that one should use predictive and prescriptive data on big data. A vast amount of data, classified and grouped, running analytics to predict what will be the next event that one or more elements of the group will take. Predictive analytics like this allows pushing of right products to e-commerce shoppers. I am sure you all have experienced this on the large e-commerce site and enjoyed it.
The simplest, easiest and spreadsheetble (I just invented this word) information which can be used for predictive and forecasting is defined data over a period. For example, date or time driven patterns which keep repeating till the cows come home. We will not discuss this here and hope you are relieved of some scepticism about this article at this stage.
