AI-Enabled Analytics and Business Intelligence Has Its Benefits

Why Choose BI Tools and Analytics with AI?

Today, the use of Artificial Intelligence (AI) has a wealth of potential and prospective application in the field of analytics and its integration within analytical products provides numerous benefits to the business. There are many ways in which artificial intelligence (AI)  can augment the capabilities of existing analytics solutions, and provide additional insight, support and results.

 

World-renowned technology research firm, Gartner, predicts that ‘40% of application development teams will be using automated data science and machine learning services to build models and add AI capabilities to applications.’

 

True to this prediction, many business intelligence and analytics solution vendors have added AI capabilities to self-serve analytics to create an environment that encourages productivity, fact-based decisions and efficient business processes, approval processes, automated alerts, etc.

 

There are a number of ways that artificial intelligence can enhance and improve the features and functionality within an enterprise using the augmented analytics environment:

Business Intelligence (BI) – Artificial Intelligence can be used to analyze large datasets and to sort and present data to achieve actionable insight, recommendations and suggestions, spotting trends, providing forecasts and optimizing results.

Generative AI (GenAI) Applications – Using Natural Language Processing (NLP) and Machine Learning (ML), AI tools can create content including images, text, video and other components to enhance presentation, interact with customers and suppliers in a targeted way and personalize messages.

Analytics Tools and Techniques – Team members and end-users can leverage self-serve analytics with AI to identify patterns and trends, gain insight, present data in a way that is meaningful to a particular target audience, predict outcomes, analyze customer buying behavior and analyze performance of products, services and other operational components.

Marketing and Advertising – The organization can analyze data from disparate data sources to identify market trends, changes in targeted customer preferences, requirements for customer relationship management, and other factors that relate to competitive advantage and customer retention.

Analytics Features and Development – Vendors and solution providers can use AI to quickly and easily upgrade analytics solutions, add features and functionality and reduce development time to keep up with client and market demands.

 

Current Artificial Intelligence technologies like ChatGPT, GenAI, and Agentic AI all provide specific capabilities to satisfy business requirements and inform and improve analytics with data gathered from within the organization that can be repurposed, targeted and used to solve problems, identify opportunities, present data to management, partners and customers, and communicate with all stakeholders using relevant data and information garnered from within and outside the enterprise.

Choose Business Intelligence and Augmented Analytics with Artificial Intelligence to Improve Outcomes
  • Improve Data Visualization – Create interactive dashboards, graphs and charts to help users present and share data in a way that is meaningful to a particular audience, and to clearly present data for confident decision-making. It can recommend and suggest visualization techniques to improve and refine how data is presented.
  • Improve Analytics with Task Automation – Automate activities and tasks, using customized automation scripts, and baseline filters and rules to extract and present data that meets user parameters. It can schedule and produce repetitive reports, and scripts can be altered change parameters, thereby freeing users to perform other operational or more strategic activities.
  • Predictive Analytics – Create predictive models using self-guiding UI wizard and auto-recommendations for swift, effortless forecasting and predictive analytics using data from numerous data sources.
  • Natural Language Processing (NLP) – Expand the capabilities of text generation and human language processing. It can enhance low resolution images, recognize and synthesize images and generate images for creative presentation of data and information.
  • Auto Insights and Machine Learning – Automates the process of interpreting and presenting results using rich visualization techniques, and includes all salient details, so users can review, share or edit content as they please.
  • Automated Alerts – Analyze results and trigger and generate alerts to protect against security violations, fraud and other risks, by analyzing normal behavior and results and comparing it to current and real-world results to identify anomalies.
  • Reporting – Using visualization, graphs, images and combining those with summaries and details can provide reports and presentations that are clear and suitable for all audiences, including management and executives, as well as teams and staff members.
  • Interpretation and Summarization – Quickly interpret and summarize data without spending a lot of time creating content, editing and preparing.
  • Data Preparation – Improve data transformation and cleansing and help prepare data and improve the quality of that data using phonetics for clustering, identifying data types, and hierarchies, suggesting alternate values etc.
  • Support for Citizen Data Scientists – Use AI cutting-edge tools to support team members with sophisticated, intuitive tools that leverage artificial intelligence (AI) and analytical techniques to produce concise results without requiring the skills of Data Scientists.

 

The analytical solutions market is moving quickly to adopt Artificial Intelligence and if your business wishes to succeed, it too must move to find and improve products and services as quickly as possible to meet customer expectations and to satisfy the ever-changing landscape of business competition.

 

Select and implement an Augmented Analytics Solution With Artificial Intelligence (AI) components to ensure affordable, flexible solutions that every user can leverage, no matter their skillset or technical capabilities. Read White Papers, ‘Generative AI (GenAI): The Benefits And Applications Of AI In Analytics,’ and ‘The Practical Use Of GenAI In Business Intelligence And Analytics Tools’ and explore the benefits of AI in analytics and the full spectrum of benefits and advantages of current artificial intelligence (AI) technologies.

 

Original Post : AI-Enabled Analytics and Business Intelligence Has Its Benefits!

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

Give Your Business Users Assisted Predictive Analytics!

Assisted Predictive Modeling Enables Business Users to Predict Results with Easy-to-Use Tools!

Gartner predicted that, ‘75% of organizations will have deployed multiple data hubs to drive mission-critical data and analytics sharing and governance.’

With all of this business data, how can your organization a) help your team gather and use data to make fact-based decisions, and b) use that data to predict which products and services your customers will need in the future, how your customer buying behavior is shifting, how your competition will respond to the market, when and how to sell your products, which marketing campaigns will work in the future, and how and when to recruit new resources and open new locations.

‘Giving your team access to sophisticated, complex analytical techniques in an intuitive environment, allows them to leverage predictive analytics without a data scientist or analytical background.’

A misstep in any of these areas can create risk, damage your business reputation, or put you years behind your competition. That’s why your business needs predictive analytics. And, not just any predictive analytics! If you want to democratize data among your team members and provide easy-to-use tools to encourage user adoption and enable data-driven decisions, you must choose wisely.

Leverage Predictive Analytics for Every Business User

Assisted predictive modeling can take the guesswork out of analytics, by helping users to choose the right techniques to analyze the type and volume of data they use to analyze. These tools allow the organization to apply predictive analytics to any use case using forecasting, regression, clustering and other methods to analyze an infinite number of use cases including customer churn, and planning for and target customers for acquisition, identify cross-sales opportunities, optimize pricing and promotional targets and analyze and predict customer preferences and buying behaviors.

Prescriptive analytics for regression models combines predictive modeling and optimization techniques to produce actionable recommendations for decision-making. While descriptive and predictive analytics use past events to predict future outcomes, prescriptive analytics goes beyond this process to recommend optimal actions that will help the business to achieve specific goals. By merging prediction with prescription, the enterprise can proactively identify challenges and opportunities, and drive more effective and strategic outcomes.

These are just some of the tools your business should consider to build a solid foundation for predicting outcomes using historical and forward-looking data analytical techniques.

Giving your team access to sophisticated, complex analytical techniques in an intuitive environment, allows them to leverage predictive analytics without a data scientist or analytical background. Your users can access:

  • Time Series Forecasting
  • Regression Techniques
  • Classification
  • Association
  • Correlation
  • Clustering
  • Hypothesis Testing
  • Descriptive Statistics

‘Assisted predictive modeling can take the guesswork out of analytics, by helping users to choose the right techniques to analyze the type and volume of data they use to analyze.’

With the right predictive analytics solution, your business can also support data scientists, IT and business analysts with tools that allow for R script integration, so these users can perform complex statistical and predictive analysis and reporting to support strategic organizational needs.

Smarten Assisted Predictive Modeling will support your team with tools that are intuitive and easy to use and will encourage user adoption.  Leverage the essential components of Augmented Analytics and improve decision-making and outcomes.

Original Post : Leverage Predictive Analytics for Every Business User!