Predictive Analytics Supports Citizen Data Scientists!

Use Predictive Analytics for Fact-Based Decisions

Like every other business, your organization must plan for success. In order to do this, the team must have a dependable plan and be able to forecast results and create reasonable objectives, goals and competitive strategies. These plans and forecasts will support investment in technology, appropriate resources and hiring strategies, additional locations, products, services and marketing strategies, partnerships and other components of business management to ensure success.

Forecasting and planning cannot be based on opinions or guesswork. It must be based on historical data, facts and clear insight into trends and patterns in the market, the competition and customer buying behavior. To accomplish these goals, businesses are using predictive modeling and predictive analytics software and solutions to ensure dependable, confident decisions by leveraging data within and outside the walls of the organization and analyzing that data to predict outcomes in the future.

‘Every industry, business function and business users can benefit from predictive analytics.’

According to CIO publications, the predictive analytics market was estimated at $12.5 billion USD in 2022 and is expected to reach $38 billion USD by 2028.

Predictive Analytics is Beneficial for Every Industry and Business Function

Predictive analytics encompasses techniques like data mining, machine learning (ML) and predictive modeling techniques like time series forecasting, classification, association, correlation, clustering, hypothesis testing and descriptive statistics to analyze current and historical data and predict future events, results and business direction.

When a business selects predictive analytics tools that are suitable for business users and team members, it can leverage sophisticated algorithms and analytical techniques in an easy-to-use environment to enable every team member to contribute to the bottom line by allowing them to gain insight into data and use that insight to make confident, fact-based decisions.

With these tools, users can explore patterns in data and receive suggestions to help them gain insight on their own without dependence on IT or data scientists. The enterprise can provide the tools needed at every level of the organization with tools and data science for business users that are sophisticated in functionality and easy-to-use for users at every skill level.

The benefits of augmented analytics and self-serve predictive modeling include:

  • No complex algorithms or data manipulation
  • Auto-recommendations for algorithms to explore underlying data
  • No advanced data science skills required
  • Analyze, share, collaborate and optimize business potential
  • Business users can prototype and hypothesize without professional assistance
  • Recommend optimal actions to achieve specific goals

Every industry, business function and business users can benefit from predictive analytics. Here are some examples of the use of predictive modeling:

Retail – Predictive Analytics tools can be used to understand customer buying behavior and to suggest products and product bundling based on previous purchases, buying patterns, and demographics. This creates a more personalized and targeted shopping experience that is unique to each customer.

Supply Chain – The organization can forecast demand and manage the supply chain to optimize inventory using machine learning to predict customer demand, seasonality, product trends etc., to that the enterprise can mitigate stock shortages and avoid warehouse and inventory overstock.

Healthcare – By using historical data regarding specific diseases, conditions and treatment plans, providers can forecast treatment outcomes, limit risk and improve overall care, thereby reducing complications, readmission and provider resource, medication and hospital bed shortages.

Energy Infrastructure – Using predictive analytics allows these businesses to monitor and analyze data and performance and to detect patterns and trends that may indicate downtime, breakdowns and maintenance issues.

Financial Services, Banks and Loan Businesses – Predictive analytics provides support for credit risk and fraud mitigation and allows businesses to create scoring models for loan approval, etc. based on credit history, and other financial considerations. Predictive modeling allows the organization to identify transactions that are outside the norm, and alert the business and its customers of hacks, fraud, etc.

‘When a business selects predictive analytics tools that are suitable for business users and team members, it can leverage sophisticated algorithms and analytical techniques in an easy-to-use environment to enable every team member to contribute to the bottom line by allowing them to gain insight into data and use that insight to make confident, fact-based decisions.’

These are just some of the benefits and use cases your business can consider to decide on how best to implement predictive analytics and integrate the use of these tools into day-to-day use for business users to improve data-driven decisions and results.

To find out more about AI And Predictive AnalyticsContact Us. Keep pace with changing enterprise needs and support business agility. Let us help you realize your business goals and objectives with fact-based information, and flexible, scalable technology solutions that will support Citizen Data Scientist initiatives, and improved data literacy and data democratization.

Original Post : Predictive Analytics Supports Citizen Data Scientists!

Auto Insights: The Secret Weapon for Analytical Results

Auto Insights: Clear and Concise Analytics

Gartner predicts that ‘organizations that offer users access to a curated catalog of internal and external data will derive twice as much business value from analytics investments as those that do not.’ In order to make the most of the data that resides in all the corners of your enterprise, you must make sense of that data, and leverage it to create products and services, to compete in your market of choice and refine your workflow and tasks to improve productivity and agility.

The key to making the most of your data is analytics, and the ability to gather and analyze data and produce results that are intuitive and clear. Machine learning has evolved to support the average business user with tools and techniques that make it easier to gather and analyze data using simple techniques that are supported by analytical techniques, without requiring business users to have data science skills.

‘Auto Insights analytics allows business users to select the dataset to be analyzed, and let the system do the rest.’

Today’s business users expect to have access to software solutions and techniques that are easy to understand and navigate. As consumers, they have the world at their fingertips, with simple techniques that require little to no technical knowledge. If your enterprise plans to adopt augmented analytics tools and business intelligence techniques, it must provide simple tools that are easy enough for the average business users to incorporate into workflow and tasks. This approach will help the organization achieve its analytical goals while ensuring an appropriate return on investment (ROI) and decreasing Total Cost of Ownership (TCO). It can also encourage and enable Citizen Data Scientist initiatives and improve data literacy.

Business Users Can Leverage Auto Insights to Easily Analyze Data

The Auto Insights approach to analytics provides a foundation of Assisted Predictive Modeling and easy-to-use tools, making it simple enough for every business user to adopt as an important tool in the team toolkit, and supporting the path from business user to Citizen Data Scientist, with tools that encourage data literacy.

Auto Insights frees business users and reduces the time and skills required to produce accurate, clear results, quickly and dependably, using machine learning that frees the business user to collect and analyze data with the guided assistance of a ‘smart’ solution.

Auto Insights allows business users to select the dataset to be analyzed, and let the system do the rest. The tool will interpret the dataset, select important columns of data, analyze its type and variety and other parameters and then use intelligent machine learning to automatically apply the best algorithm and analytical technique and provide data insight so the user can easily see and understand the results.

The Auto Insights concept is applied to data repositories to enable the enterprise and its business users to perform complex data analytics and share analysis across the organization in a self-serve, mobile environment, bringing the power of sophisticated, advanced analytics and smart data visualization to the members to automate and analyze, so enterprise users can quickly get the answers they need and move on to make confident decisions.

‘The key to making the most of your data is analytics, and the ability to gather, analyze and view data easily, and produce results that are intuitive and clear.’

If you are interested in finding out more about the advantages of the Smarten Auto Insights approach to Augmented Analytics and self-serve search analytics, Contact Us to explore how these techniques can help your enterprise apply analytics to achieve results. Let us help you realize your business goals and objectives with fact-based information.

Original Post : Auto Insights: The Secret Weapon for Analytical Results

Understanding and Addressing Data Anomalies in Business!

How Can My Business Understand and Handle Those Pesky Data Anomalies?

Why guess at the cause of your business results? Whether you are seeing positive or negative results, it is still important to understand the ‘why.’ Without this information, you cannot adapt and adjust to improve declining results, OR repeat and improve those great results you are experiencing.

Augmented Analytics Must Provide Data Quality and Insight!

How Can I Ensure Data Quality and Gain Data Insight Using Augmented Analytics?

There are many business issues surrounding the use of data to make decisions. One such issue is the inability of an organization to gather and analyze data. These enterprises will typically focus on building a team of data scientists or business analysts to help with this task OR they might take on an augmented analytics initiative to provide access to data and analytics for their business users. This is where businesses will often face a second issue; namely that the analytics solution they choose is not designed to easily and quickly provide insight into data and to ensure data quality.

Business Users CAN Use Predictive Analytics!

Predictive Analytics is a Critical Component of an Augmented Analytics Suite!

Analytics and advanced analytics techniques can seem daunting to the average business user but they need not be. If a business wants its users to adopt and use analytics tools, an augmented analytics solution is the way to go. These solutions are easy to use and provide guidance and auto-recommendations to help users gather and analyze data using the right analytical technique.