Skip to main content

Predictive Analytics for Business Users!

Can Business Users Adopt Assisted Predictive Modeling?
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.
Plug n’ Play Predictive Analysis can truly provide predictive analytics for business users and predictive analytics can benefit organizations in many ways. Whether you want to find out how best to acquire and retain customers, what new products and services your customers want, how to price a product, where to open a new location, or how your customer purchasing behavior is changing, predictive analysis can help you understand historical patterns and use your data and results to more accurately predict the future.
In the past, business users struggled to understand the relationship between their roles and responsibilities and the results the organization achieved. If you empower your business users with easy-to-use, sophisticated predictive analytics, you can cascade and share strategic, operational and tactical goals and enable users to share data and use that data to make better decisions.
Your business users are not data scientists, nor should they have to acquire and use sophisticated skills to get the answers they need. With real self-serve, Predictive Analysis Tools, business user can apply complex predictive algorithms without the expertise and skill of a trained data scientist or the assistance of IT staff. With these tools, business users will become more of an asset to the organization and you can transform every team member into a Citizen Data Scientist and employ their unique professional skills and knowledge to gather and analyze data in a way that is meaningful to their role and their assigned tasks and activities.
No matter how small or large your business, and no matter your industry, your organization cannot afford a market or competitive misstep. There is no time to guess at the future. But, with the right tools to build the right plan and anticipate product, service, pricing, distribution, location and customer changes and evolution, your business can accurately plan for success.

Comments

Popular posts from this blog

Orchestrating Growth

The  Interactive Symphony of Digital Transformation and Leadership In a world where candle makers evolved into bulb manufacturers and carriage-makers transformed into car producers, the relentless tide of digitization silently reshapes industries. We stand on the precipice of a transformative era, where technology intertwines with data, analytics, and robotic process automation.   As the maestros of this digital symphony, Dataception explores the multifaceted forces driving innovation. Today, we embark on a journey through the realms of leadership, data-driven decision-making, and the creation of value. The Unseen Revolution: Digitization, like a silent revolution, reshapes structures imperceptibly. Comparable to the transition from candles to bulbs, this shift is profound, often escaping immediate notice. In this transformative era, technology is not merely a tool but the very medium through which industries communicate, evolve, and thrive. The Evolution of Demand: ...

Platform engineering : A Catalyst for Growth

Platform engineering is a discipline that focuses on building and maintaining internal developer platforms (IDPs). IDPs are a set of tools and services that provide developers with a self-service environment for building, deploying, and monitoring applications. Platform engineers work closely with developers to understand their needs and build an IDP that meets those needs. They are responsible for designing, building, and maintaining the IDP architecture, as well as developing and maintaining the tools and services that are offered on the platform. It is a relatively new discipline, but it has quickly become essential for software engineering organizations of all sizes. As organizations adopt cloud-native architectures and DevOps practices, they need a way to provide developers with the tools and services they need to be productive.  Some of the key benefits of platform engineering include: Increased developer productivity: It can help developers be more productive by providi...

Why Do You Need Self-Serve Data Preparation?

Self-Serve Data Preparation Takes the Headache Out of Data Analytics! 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. Business users love  Self-Serve Data Preparation  because they can control data elements, and the volume and timing, perform data preparation and test theories and hypotheses by prototyping on their own. No one likes to be restricted to complex tools or forced to wait for programmers or data scientists. Give your business users access to crucial data and connect them to data sources so they can mash up and integrate data in a single, one-st...