Predictive Analytics used to involve a crystal ball but, today, there are other options and they are more widely accepted in the business community! With the right predictive analytics tool, your business can hypothesize, test theories, discover the effects of a possible price increase, discover and address changing buying behavior and develop appropriate competitive strategies.
The process of predictive analytics has come far in the past decade. No longer is this process the sole responsibility of data scientists or IT staff. Today’s self-serve predictive analytics and forecasting tools are designed to support business users and data analysts alike.
This article provides a brief explanation of the Holt-Winters Forecasting model and its application in the business environment.
Even if you do not work in IT, you have probably heard the term ‘Big Data’. These days, Big Data can cause big problems. If you do not have a plan to manage all that data and to make it easily accessible to your users, the data may as well not exist. If you cannot use that data for predictive analytics, you cannot accurately forecast your business results, plan for growth or compete in the market.
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.
Today, enterprises recognize the critical value of advanced analytics within the organization and they are implementing data democratization initiatives. As these initiatives evolve, new roles emerge in the organization. The newest of these analysis-related roles is the ‘analytics translator‘. As the enterprise considers the relevance of this new role within the business, it is important to understand the responsibilities of an Analytics Translator, and how this role might help the organization to achieve its goals.
You may think your business is unique (and it is) but in lots of ways, it is just like mine. Here’s what I mean. Every enterprise, including yours, desperately needs dependable, accurate data to support decisions and planning processes. So, in that way, all businesses are the same. Whether data analysis requirements are ongoing or specialized to support a focused initiative, the challenges of advanced data analytics and data science efforts can be daunting.
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.
