Tag: Assisted Predictive Modeling

Citizen Data Scientists Need These 3 Things to Succeed!

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March 5, 2024

3 Primary Components for Citizen Data Scientist Success!

The Citizen Data Scientist phenomenon is in full swing and, while the approach has its detractors, the proof is in success, and many organizations are actively succeeding using the Citizen Data Scientist approach.

Gartner has predicted that, in the future ‘…40% of data science tasks will be automated, resulting in increased productivity and broader usage by citizen data scientists.’

‘The enterprise does not expect to hire a legion of data scientists to perform analytics for every day-to-day need within the organization.’

There are many benefits of transitioning business users to a Citizen Data Scientist role, including:

  • Improved data literacy
  • Increased Data Democratization
  • Improved Collaboration
  • Increased Productivity
  • Improved Alignment with Goals and Objectives
  • Optimization of Data Scientist and IT Resources
  • …and more!
3 Keys to Citizen Data Scientist Success

There are many factors and components inherent in the success of a Citizen Data Scientist. If you are a Citizen Data Scientist candidate, there are three primary components of success:

  1. Organizational Commitment and Support – A business cannot just say they are committed to the Citizen Data Scientist approach. It must plan carefully and include a complete review of the current workflow, business processes and technology in order to make the changes required to support the new program. Citizen Data Scientists must be supported with revisions to performance evaluations and promotions. These revisions should encourage and enable the use of augmented analytics and collaboration so that business users are rewarded for acquiring and using new skills.
  2. Appropriate Augmented Analytics Tools – As with any other type of position or job, a Citizen Data Scientist needs the right tools to succeed. Without the right analytics tools, business users cannot make a successful transition to a Citizen Data Scientist role. The enterprise does not expect to hire a legion of data scientists to perform analytics for every day-to-day need within the organization but, if business users are expected to perform analytical activities, they will need easy-to-use tools that are sophisticated enough to achieve results, without requiring complex analytical skills or lengthy training. Augmented Analytics tools that are designed for business users should provide a foundation of machine learning and natural language processing (NLP) so search analytics is as easy as asking a question in a Google-type interface, with features like Smart Data Visualization, Assisted Predictive Modeling and Self-Serve Data Preparation.
  3. Curiosity and the Willingness to Explore – A prospective Citizen Data Scientist should have at least an average technology capability, with above average curiosity and a willingness to learn and collaborate. The ideal candidate should be recognized as someone who interacts well with others, and is willing to mentor others and help them become comfortable with new tools and processes.

‘If you are a Citizen Data Scientist candidate, there are three primary components of success.’

These are just a few of the factors you must consider when implementing a Citizen Data Scientist approach. Business users who are interested in becoming a Citizen Data Scientist must be willing to embrace new technology and tools and working at the leading edge of a new approach to collaboration and decision-making. initiative. Consider engaging an expert for your Citizen Data Scientist. IT consultants with experience and skill in this area can provide crucial support to help you succeed with your Citizen Data Scientist initiative and can provide simple Training Programs to bring your team on board and help them see the value to themselves and to the organization.

Original Post: Citizen Data Scientists Need These 3 Things to Succeed!

Smarten Augmented Analytics is Named as a Representative Vendor in Gartner® 2023 ‘Market Guide for Augmented Analytics, Published October, 2023!

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November 23, 2023

Smarten is pleased to announce that its Smarten Augmented Analytics solution is included as a Representative Vendor in the Market Guide for Augmented Analytics Published October 2, 2023 (ID G00780764).

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Should I Start a Citizen Data Scientist Program?

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October 4, 2023

Is it the Right Time for My Business to Initiate a Citizen Data Scientist Program?

Whether you are a business owner, a business executive or a business manager, or you just like to keep up with industry trends, you no doubt have read about the transition of business users to Citizen Data Scientists. The topic has been in industry journals and publications for years, and it is still relevant today.

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Support Enterprise Agility with the Right Self-Serve BI Tools!

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April 6, 2023

Enterprise Agility and Adaptability Are Crucial. The Right BI Tools Can Help!

Gartner research states that, ‘90% of corporate strategies will explicitly mention information as a critical enterprise asset and analytics as an essential competency.’

Whether yours is a small or a large business, your success today depends upon your agility and adaptability and those characteristics also apply to your data and your information.

If you are to build a flexible business environment, you must have tools and solutions that allow you to monitor and manage data and information and use that data to make fact-based decisions.

‘Comprehensive BI Tools should provide data analytics access for all business users and, above all, provide flexible, agile solutions that can be used at all levels to collaborate, share data and report and communicate with clarity.’

When considering a business intelligence (BI) solution, choosing a self-serve tool serves two purposes:

Choose Self-Serve BI Tools to Support Business Success

Support for the Organization and Users

A business can provide software and tools for users, but if those tools are not user-friendly, or if team members do not perceive their value, they will not adopt the solution into their business processes. In order to ensure that the organization can expect a good return on investment (ROI) and a low total cost of ownership (TCO), the enterprise must select a BI tool that is useful to the team and can easily be applied to satisfy the needs of their role and their responsibilities. The tools must also provide self-serve tools that offer comprehensive predictive analytics, key performance indicators (KPIs), flexible reporting, self-serve data preparation, deep dive analytics, mobile BI and social BI. This foundation will allow business users to improve data literacy and perform analytics with confidence, thereby improving fact-based decision-making.

Flexibility and Agility

When the organization selects business intelligence tools that are flexible, users can leverage personalized dashboards and customize their use to serve the needs of their role, their team and their business unit. The ability to adapt quickly by finding the root cause of a problem, spotting a trend and addressing that trend or identifying an opportunity to improve competitive advantage can provide an edge in the market and allow the organization to move quickly. Users can collaborate and share data to make decisions and recommendations and suggestions are clearly supported by data, so there is no hesitation or delay.

‘If you are to build a flexible business environment, you must have tools and solutions that allow you to monitor and manage data and information and use that data to make fact-based decisions.’

Comprehensive BI Tools should provide data analytics access for all business users and, above all, provide flexible, agile solutions that can be used at all levels to collaborate, share data and report and communicate with clarity. Simple, Self-Serve BI Tools can provide your business with the foundation to achieve your data democratization and user adoption goals. Let us help you achieve your vision and improve productivity and insight across the organization.

Original Post : Choose Self-Serve BI Tools to Support Business Success!

Predictive Analytics Business Use Cases Ensure Results!

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September 27, 2022

Apply Predictive Analytics to Specific Business Use Cases for Real Results!

Gartner has predicted that, ‘Overall analytics adoption will increase from 35% to 50%, driven by vertical and domain-specific augmented analytics solutions.’ Your business, like every other business in the world, has its own industry, domain and vertical concerns, and these concerns drive your competitive strategy, your products and your services.

Predictive analytics uses sophisticated analytical methodologies to predict future outcomes based on historical data. Using these techniques, the organization can predict future events, customer buying behaviors, and business outcomes. These techniques can help the business drive results, improve revenue, understand customer and client buying behavior, solve problems, plan for new locations and products, create accurate pricing strategies and plan for new resources and training, as well as for appropriate maintenance, supply chain services, etc.

‘Take the guesswork out of the planning process and analyze factors that influence business success. Plan and forecast accurately.’

Predictive Analytics utilizes various techniques including association, correlation, clustering, regression, classification, forecasting and other statistical techniques. These techniques can be targeted to specific business use cases to solve specific, unique business issues and to help the business plan, forecast and compete.

In order to understand how businesses might use assisted predictive modeling and predictive analytics, let’s look at some business use cases and how analytical techniques can help the enterprise derive concise, clear information to support decisions and strategies.

Minimum Viable Products (MVP) Produces Better Business Start-Up Results

Customer Churn

The cost of acquiring and interacting with customers can be expensive and each time a business loses a customer, it must spend money to replace the customer.

Fraud Mitigation

Businesses must mitigate fraud and control business costs and must develop and sustain fraud detection processes to monitor operations.

Quality Control

Businesses must control quality or risk losing customers and market share and exposing the enterprise to legal risk and liability.

Demand Planning

Take the guesswork out of the planning process and analyze factors that influence business success. Plan and forecast accurately.

Product/Service Cross-Selling

Leverage customer satisfaction to cross-sell and upsell products and services and increase revenue and brand loyalty.

Maintenance Management

Focus on equipment maintenance to ensure that downtime is limited and equipment is up and running, anticipate resources, hours on the job and training needs.

Customer Targeting

Identify the reasons customers buy a product or service and use fact-based data to create products, marketing campaigns, ads and customer outreach. Target specific demographics and customers.

Human Resource Attrition

The enterprise must retain team members and to do so, it must understand what makes a team member stay or go, what makes them invest in the future of he business and what issues create issues and dissatisfaction.

Loan Approval

The enterprise must avoid bad loans, so as to enhance profitability and productivity and it must have a dependable process for identifying and attracting the right clients and for reviewing, approving and managing loans.

Marketing Optimization

Create attainable targets and goals with an understanding of what improves and affects sales and how customers choose a product or service, how to market and advertising to achieve objectives.

Predictive Analytics Using External Data

Integrate external data and analyze data to assess the affect on sales, marketing, finances, resources, productivity, etc.

Online Target Marketing

Optimize marketing funds and resources, understand what works and what does not work, and how, when and where to message and the ideal demographic and profile of the target customer.

Student Academic Performance

Predict academic performance of students to effectively manage student interaction and training and improve environment to assure student success.

Crime Type Prediction

Predict the type of crime that is likely to occur to plan for appropriate law enforcement resources, placement and strategies and ensure public safety and appropriate use of funds.

‘Predictive Analytical techniques can be targeted to specific business use cases to solve specific, unique business issues and to help the business plan, forecast and compete.’

Find out how Assisted Predictive Modeling and Augmented Analytics can help your business plan for success, and explore the potential of comprehensive Predictive Analytics here.

Original Post : Predictive Analytics Business Use Cases Ensure Results!

Get the Right Predictive Analytics Tools for Users!

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August 5, 2022

Can Predictive Analytics Provide Accurate Results for My Business Without Burdening My Users?

If your business is struggling to forecast and predict outcomes and results, your management team is probably considering predictive analytics. The technology research firm, Gartner, states that, ‘50% of data scientist activities will be automated by artificial intelligence, easing the acute talent shortage.’

For the average team member, the concept of predictive analytics may seem daunting and, if you are a business user whose management team has asked you to embrace and participate in analytics, the addition of predictive analytics to your day-to-day business processes may seem irrelevant or it may seem to mean you will be expected to work harder or produce more output. But don’t be too quick to assume the worst.

‘By providing this type of expanded functionality to the team, the business can enable both data scientists and business users with predictive analytics that will benefit the organization.’

Let’s take a look at Predictive Analytics, the benefits of Assisted Predictive Modeling and its importance in the organization and how intuitive augmented analytics can help business users achieve their goals without requiring advanced training or additional workload.

Predictive Analytics Can Make Business Users Happy!

What is Predictive Analytics?

Predictive analytics is comprised of sophisticated analytical methodologies that allow businesses to predict future outcomes based on historical data. Using these techniques, the organization can predict future events, customer buying behaviors, and business outcomes. Predictive Analytics utilizes various techniques including association, correlation, clustering, regression, classification, forecasting and other statistical techniques.

Understanding Assisted Predictive Modeling

When a business provides augmented analytics tools for business users, it allows the team to perform predictive analytics on a daily basis without the assistance or skills of a Data Scientist or an IT professional. Assisted Predictive Modeling provides auto-suggestions and recommendations to guide business users with recommended techniques, selecting the most appropriate techniques for the type and volume of data the user wishes to analyze. If the business chooses an augmented analytics tool with intuitive predictive modeling features, it allows users to work quickly and receive clear, concise results for decision-making so user adoption of the tools is more likely and forecasting and predictions are accurate and timely. All popular predictive modeling techniques are incorporated into the solution, so users have access to the most sophisticated predictive analytics and tools and can use these tools to model and review business use cases and issues.

The Benefits and Importance of Assisted Predictive Modeling

These tools allow the organization to apply predictive analytics to real use cases to analyze customer churn, to target customers, to identify cross-selling and product bundling, to find and set appropriate price points, to forecast where and when to open new locations, when the business will need new suppliers, when equipment will require maintenance, etc. A comprehensive augmented analytics solution also includes the benefit of integration with R Script, so that data scientists can capitalize on expertise and leverage enterprise investments in R open-source platforms, to perform statistical and predictive algorithms, and complex analysis to provide the depth of detail and advanced analytics and reporting the organization needs for strategic decision-making. By providing this type of expanded functionality to the team, the business can enable both data scientists and business users with predictive analytics that will benefit the organization, encourage collaboration and data sharing, and improve data literacy – all without increasing workload or frustrating users and team members.

‘Intuitive assisted predictive modeling and augmented analytics can help business users achieve their goals without requiring advanced training or additional workload.’

Find out more about Assisted Predictive Modeling and Augmented Analytics and explore the potential of comprehensive Predictive Analytics here. Find out how it can improve user adoption of analytics and increase accuracy of forecasting and results.

Original Post : Get the Right Predictive Analytics Tools for Users!

Embedded BI Can Encourage Data Literacy!

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June 22, 2022

Technology research and consulting firm, Gartner, predicts that, ‘By 2023, data literacy will become an explicit and necessary driver of business value, demonstrated by its formal inclusion in over 80% of data and analytics strategies and change management programs.’

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Assisted Predictive Modeling is Your Secret Weapon!

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January 18, 2022

Predictive Analytics That is Easy Enough for Any Business User!

Predictive analytics may seem too complex for business users but with advanced technology like machine learning and features like assisted predictive modeling users can dive into the process without the skills of an IT professional or a data scientist. Assisted predictive modeling frees the user by providing system recommendations that will suggest the right analytical technique and achieve the best fit for what the user wants to do, ensuring that they use the most appropriate algorithm for the data they wish to analyze.

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BI Tools with R Integration Make Users Happy!

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December 9, 2021

What is R Scripting and Why Do I Need it Integrated in My BI Tool?

Don’t you hate it when someone blurts out a mysterious term at a business conference and you are left to decide whether to reveal your ignorance by asking what they are talking about, or simply nodding your head and smiling as if you understand and agree? I hate it when that happens.

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Insight and Perspective: The Gifts of Augmented Analytics!

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December 1, 2021

Augmented Analytics: Insight Comes from Perspective!

Perspective is everything. You can stare at numbers and columns all day and never see the one nugget of information that will give you insight and help you solve a problem or find that one opportunity to drive the business to the next level. When you and your business users can leverage augmented analytics tools, without worrying about complex algorithms or writing code or designing reports, you can find those elusive nuggets of information and use them to improve your business results.

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