Tag: Assisted Predictive Modeling

Enhance BI Tools and Analytics with Low-Code, No-Code Development!

author_img
by |
January 6, 2025

BI Tools and Analytics with Low-Code, No-Code Features!

Whether your team is currently using traditional business intelligence, or augmented analytics tools, or you are planning to implement your first analytics solution, it is important to understand the relevance of low-code and no-code development (LCNC) and LCNC features and techniques to your team and your selected analytics solution.

Analytics with business intelligence and low code no code go hand-in-hand. The solution you choose can and should include both standard BI tools and sophisticated augmented analytics.

The global technology research firm, Forrester highlights the complexity of existing technology environs, and the importance of supporting the business with agile, adaptable tools and workforce and suggests that low-code/no-code development allows organizations to accelerate innovation and increase business agility and sustainability.

‘By integrating this approach within the business intelligence and augmented analytics environment the business can eliminate the need for expert programmers and IT professionals and allow team members to perform simple analytical, reporting and visualization tasks and create and explore analytics without the assistance of consultants or IT staff.’

When we add a low code no code complement to this environment, we integrate simple technology that allows the analytics solution to keep pace with your changing organization while enabling data sharing and user adoption so the enterprise can produce fast, dependable insights and improve the value of business analysis across the enterprise, and democratize the use of advanced analytics.

How Can Low-Code, No-Code Development Enhance BI Tools and Predictive Analytics?

To further illustrate how low code and no code development can be leveraged in BI tools and analytics, let’s look at some examples of how LCNC can be integrated within the analytics environment to improve, enhance and innovate analytics features and functionality.

Data Preparation, Transformation and Cleaning

Connect to multiple data sources, clean and transform data using intuitive visual tools, wizards, data pipeline charts and configuration, without the need to create complex extraction, transformation and loading (ETL) scripts.

Data Visualization

A drag and drop smart visualization engine allows the user to select the best fit and most appropriate options to visualize a particular dataset based on data columns, types, data volume and other factors.

Self-Serve Reports, Graphs and Dashboards

The team can leverage self-serve tools and wizards with drag n’ drop features to create dashboards, reports and summaries, to pivot and unpivot data, to add columns, spot lighters, and other features to enhance and clarify data presentation.

Predictive Modeling

A wizard-based, guided user interface (UI) helps users to create predictive models with no need for IT intervention, and no programming or scripting experience. The system will suggest the best-fit algorithm for the data the user wishes to analyze and fine tune parameters to create accurate, appropriate predictive models.

Anomaly Alerts

Key Performance Indicators (KPIs) are configured with simple or complex expressions, thresholds and frequencies, using a wizard-based user interface (UI), so the team can achieve swift results without IT intervention.

Expressions

An easy-to-use expression engine leverages functions and syntax with examples and test/validation features for key performance indicators (KPIs), new columns and other areas where expressions are required.

BI Platform Administration

The Application Administrator is a 100% graphical user interface (GUI) system that allows for platform and application management without scripting.

User Access Rights and Permissions

Configure and manage user access rights without scripting or programming using a 100% graphical user interface (UI) approach.

Embedded BI

Optimize application integration with easy-to-use Application Programming Interfaces (API) to embed BI objects and predictive models within third-party applications, and perform administrative tasks including user management and user access rights management.

By integrating this approach within the business intelligence and augmented analytics environment the business can eliminate the need for expert programmers and IT professionals and allow team members to perform simple analytical, reporting and visualization tasks and create and explore analytics without the assistance of consultants or IT staff, thereby reducing dependency on data scientists and IT and enabling power users and Citizen Data Scientists.

In addition, the use of low code and no code techniques and platforms allows for improved performance, and provides the flexibility to address rapidly changing user and business requirements as well as allowing the solution vendor to quickly add features and upgrade the solution to keep it evergreen.

For a more detailed discussion of Low-Code/No-Code in Analytics, explore our complementary article, ‘The Use And Benefits Of Low-Code No-Code Development In Business Intelligence (BI) And Predictive Analytics Solutions.’

‘Analytics with business intelligence and low code no code go hand-in-hand. The solution you choose can and should include both standard BI tools and sophisticated augmented analytics.’

Contact Us to find out how no code data analytics and the low code approach for business analytics can support your needs. Our Business Intelligence And Augmented Analytics solution can help your business achieve objectives. Read this free article to discover the potential of no code business intelligence software and LCNC And AI In Predictive Analytics, explore  our seamless Analytics Solution Technology. Download A Free Trial Of Smarten Analytics Software.

For a detailed discussion of Low-Code/No-Code in Analytics, explore our complementary article, ‘The Use And Benefits Of Low-Code No-Code Development In Business Intelligence (BI) And Predictive Analytics Solutions,’ ‘What Is LCNC And How Does It Change The Analytics Market?’, ‘Choose The Right LCNC BI Tools And Predictive Analytics,’ and ‘LCNC Benefits Teams, Business Users And Citizen Data Scientists.’

Original Post: Enhance BI Tools and Analytics with Low-Code, No-Code Development!

Low-Code and No-Code Development in Analytics!

author_img
by |
January 6, 2025

Using LCNC in Augmented Analytics

Low-Code Development and No-Code Development have been getting a lot of press in technology publications and conferences of late. If you are interested in finding out more about this topic, and about how low-code, no-code (LCNC) can be used to enhance analytics and change the approach of the self-serve, augmented analytics market, this article will provide you with a primer.

‘Including the LCNC approach in BI and analytics tools can and will support the enterprise as it moves forward, and can provide advantages and support for the future.’

Let’s begin with a Definition Of Low Code And No Code, and a discussion of the difference between Low Code And No Code Development.

What is Low-Code, No-Code Development and How Is It Used in the Analytics Market?

 

Low-Code Development

Low-Code Development allows programmers and developers to quickly and easily create applications using tools that simplify the development process with drag and drop components that enable the team to add features without writing code ‘from scratch.’ This visual development approach uses a graphical user interface (GUI) to support programmers as they build applications. To understand how this benefits the development team and the business, it is important to understand how low code platform works. By enabling swift development and mitigating the use of complex code, developers can easily add features to keep pace with the market and customer needs, so upgrades and iterations are fast and easy. The low-code platform is easy to integrate with existing systems, so it will support users of popular and familiar solutions with new features that are easy to use.

No-Code Development

No-Code Development requires no coding and is used to create simple, basic applications that can be quickly deployed and upgraded. The no code environment uses a graphical user interface (GUI) that is user-friendly and easy for developers to navigate. It supports developer productivity with easy-to-use tools and is less expensive than the typical software development approach, and it is easy to customize, though it is not scalable for complex application development and will produce only limited functionality. The no-code platform is fast and easy to use and provides an additional set of tools and an approach that will support programmer productivity and get products and upgrades to market quickly.

When considering the difference between low code and no code development, here is the bottom line:

Low-Code solutions use visual development environments and automated links to back-end systems, databases, web services and APIs.

No-Code solutions utilize visual drag-and-drop interfaces and require no coding, but rather are configured and implemented quickly, using the skilled application of tools and techniques.

The top low-code platforms are easy for developers to learn and the no-code environments have a library of pre-built components from which the team can choose.

World-renowned technology research firm, Gartner, predicts that low-code development tools will account for 75% of new application development by 2026. This prediction is primarily based on what Gartner perceives as increasing pressure for businesses to adapt quickly to market and competitive trends and changes.

The global technology research firm, Forrester highlights the complexity of existing technology environs, and the importance of supporting the business with agile, adaptable tools and workforce and suggests that low-code/no-code development allows organizations to accelerate innovation and increase business agility and sustainability.

Given the recent elevated status of low-code no-code in development and low-code no-code tools, it is important to consider whether the market has responded by adopting these techniques.

According to SlashData the use of LCNC has increased from 46% to 57% over a period of eighteen (18) months, with the usage of LCNC tools estimated at:

70% Data Science

66% Machine Learning

75% Embedded Software

69% Apps and Extensions for 3rd party ecosystems

58% Mobile Apps

Many businesses have employed LCNC to step up their competitive positioning and create and innovate quickly. Examples Of Low Code And No Code Business Innovation Include Amazon, Google, Apple, Akkio, DataRobot, and Microsoft.

When we consider the use of LCNC in business intelligence (BI) tools and predictive analytics, the reason for the uptick in usage among developers and IT professionals is quite clear.

As businesses embrace data democratization and recognize the need for data literacy among team members, and as enterprises launch Citizen Data Scientist initiatives, they face numerous obstacles and challenges, including the selection of an intuitive, self-serve BI and augmented analytics solution. Finding and choosing the right solution will drive willing user adoption, improved Return on Investment (ROI) and low Total Cost of Ownership (TCO).

But the selection of the right BI and analytics solution must also include considerations for sustainability, keeping pace with team, customer and market trends and changing behaviors, and ensuring that the technology investment will serve the organization in the long term.

Including the LCNC approach in BI and analytics tools can and will support the enterprise as it moves forward, and can provide advantages and support for the future.

For a more detailed discussion of Low-Code/No-Code in Analytics, explore our complementary article, ‘The Use And Benefits Of Low-Code No-Code Development In Business Intelligence (BI) And Predictive Analytics Solutions.’

Including the LCNC approach in BI and analytics tools can and will support the enterprise as it moves forward, and can provide advantages and support for the future.’

Contact Us to find out how no code data analytics and the low code approach for business analytics can support your needs. Our Business Intelligence And Augmented Analytics solution can help your business achieve objectives. Read this free article to discover the potential of no code business intelligence software and LCNC And AI In Predictive Analytics, explore our seamless Analytics Solution Technology.
Download A Free Trial Of Smarten Analytics Software.

For a detailed discussion of Low-Code/No-Code in Analytics, explore our complementary article, ‘The Use And Benefits Of Low-Code No-Code Development in Business Intelligence (BI) and Predictive Analytics Solutions,’ ‘How Does LCNC Enhance BI and Predictive Analytics,’ ‘Choose the Right LCNC BI Tools and Predictive Analytics,’ and ‘LCNC Benefits Teams, Business Users and Citizen Data Scientists.’

Original Post: Low-Code and No-Code Development in Analytics!

Why Should Business Users WANT to be a Citizen Data Scientist?

author_img
by |
November 7, 2024

Making the Case for Citizen Data Scientists!

When a business decides to undertake a data democratization initiative, improve data literacy and create a role for Citizen Data Scientists, the management team often assumes that business users will be eager to participate, and that assumption can cause these initiatives to fail.

Continue reading “Why Should Business Users WANT to be a Citizen Data Scientist?”

Choose Augmented Analytics Designed for Business Users!

author_img
by |
September 11, 2024

Avoid Complex Analytics Solutions (Your Users Will Hate)

When a business is considering a business intelligence or analytics solution, it is important to recognize that today’s solutions are very different than the solutions of the past. Not only do they include more analytical techniques and features, but they have come a long way in providing access to sophisticated analytics for the average enterprise team member.

Harvard Business Review Analytics Service reports that

a) businesses can substantially improve business performance by giving frontline workers modern self-service analytics tools to enable fast intelligent action and,

b) not all self-service analytics provide this effective approach.

Choose Augmented Analytics Designed for Business Users and Get the Most From Your Solution

The Harvard Business Review Analytics Service surveyed nearly 500 executives and found that they reported significant performance improvement when they empowered frontline workers with augmented analytics. More than one-third of those surveyed noted improvement in customer and employee engagement and in product and service quality.

While some businesses may still be using business intelligence and analytics that are designed for data scientists and IT professionals, most of those are actively working to upgrade and/or migrate to augmented analytics and solutions that are designed for self-serve business user access.

Here’s why:

  • Search-based, self-serve analytics provides swift access to data and familiar natural language processing (NLP) search capability so business users can ask a question, get an answer and drill down to discover the root cause of issues. There is no need for the user to wait for IT or a data scientist to produce a report. They can continue to work on a task or a problem with full insight into results, challenges and possibilities.
  • The enterprise can enable data democratization and data literacy across the business landscape, thereby ensuring that there is a rapid response to market and competitive changes and to changing customer buying behavior.
  • Business users can leverage their industry knowledge and functional skillset and combine data insight with experience to produce the best results.
  • Intuitive, easy-to-use solutions help to combat user resistance and ensure user adoption. While there are always cultural issues surrounding this type of adoption and the perceived changes in responsibilities, when business users see the value of having crucial information at their fingertips, the enterprise can ease the transition and ensure user adoption.
  • No matter the role of the user, the team can enjoy the benefits of augmented analytics and make the transition to Citizen Data Scientists to improve collaboration, data sharing and fact-based decision-making.
  • The business can understand quality and maintenance issues, refine customer targeting and marketing optimization, and make appropriate financial investments, and they can analyze trends and patterns and make forecasts and predictions.
  • When the enterprise adopts these tools and techniques, they allow Citizen Data Scientists to perform analytics on a day-to-day basis and, where appropriate to effectively interact with and collaborate with the IT team and data scientists to refine data and prepare it for more strategic initiatives, so there is a seamless handoff from the business user to the analytical community, when and as necessary.

When the business is ready to acquire augmented analytics or to upgrade from existing, more restrictive solutions designed for professional analytical resources, it is important to choose the right solution – one with sophisticated tools that are presented in an intuitive user interface with auto-suggestions and recommendations to assist business users, and ample personalization of dashboards and reports.

With the right IT consulting partner, you can select and implement an Augmented Analytics Solution with business intelligence (BI) and advanced capabilities, and ensure that every user can leverage these tools, no matter their skillset or technical capabilities. Explore our free white paper, ‘A Roadmap To ROI And User Adoption Of Augmented Analytics And BI Tools.’

Original Post: Choose Augmented Analytics Designed for Business Users!

Plan Carefully for a Citizen Data Scientist Program

author_img
by |
August 30, 2024

Create a Plan for Citizen Data Scientists

The term, ‘Citizen Data Scientist’ has been around since 2016, when the world-renowned technology research firm, Gartner, coined the phrase. Whether you want to know more about the concept, understand the concept and would like to know if your business can leverage this approach to improve its market position and customer visibility, or you have embraced the Citizen Data Scientist approach and are looking for ways to expand and refine the concept within your own business environment, we are here to help.

As Gartner research states, ‘Early adopters of augmented analytics have the potential to realize more strategic and differentiating business benefits from their analytics investments than those who wait until these technologies are widely adopted.’

Planning and Preparing for a Citizen Data Scientist Initiative

One of the most important aspects of any new, large scale initiative, is preparation and when it comes to the Citizen Data Scientist approach, preparation is equally important. Let’s look at some of the primary factors and considerations you must include in your planning process.

‘Will you deploy the augmented analytics solution across the entire enterprise at once, or will you roll it out by division, department, location, etc.? Who will be in charge of the deployment?’

Review Technology and Business Processes

Look at your current technology and all the places your data resides (data warehouses, the cloud (private or public), best-of-breed software, legacy software, ERP, CRM, HR, SCM, and other focused solutions that support a particular division, team or department. You will want to integrate data from all possible sources in order to give your users the information they need to perform analytics.

Work with your IT team, and (if you have already chosen an IT consultant) with your advisors to analyze the technology and infrastructure and establish a plan of attack. Consider the network, hardware and software, and decide whether you will want Embedded BI within any popular software solution to allow users to leverage a single sign-on environment to access data and analyze it all in one place.

Review business processes, workflow, approval loops etc., and see where you can gain advantage by including analytics and technology to improve productivity and the quality and speed of decisions.

Involving Stakeholders, Customers, Users, IT, etc.

Management and/or IT cannot plan for and execute this type of change alone. You will need to understand how cascading analytics throughout the organization will impact your users, your customers and others. Establish a team that includes representatives from the various functions, levels and areas within the enterprise.

Listen to their concerns and address those concerns with an appropriate plan for deployment, training, ongoing support, etc. Otherwise, you are unlikely to succeed. User adoption is important but you can also use this time to identify and highlight those areas where you can find opportunities and thereby improve the success metrics and outcomes you hope to achieve.

Choosing an Augmented Analytics Solution

Choosing the right augmented analytics and business intelligence (BI) solution will drive success of a Citizen Data Scientist initiative. These solutions are key to helping you achieve your goals and to supporting your business users as they make the transition to Citizen Data Scientists. Look for a full suite of features and functionality to support your users.

Not all augmented analytics solutions are equal! Be sure the solution you choose has all the features you need and will be easy for your users to learn and adopt. Look for a comprehensive solution suite that includes:

Planning for Deployment

Will you deploy the augmented analytics solution across the entire enterprise at once, or will you roll it out by division, department, location, etc.? Who will be in charge of the deployment? Your team should include representatives from the various groups that have a vested interest in the outcome. When you choose an IT consultant, they can help you plan for and execute your strategy so that it is successful and you are not overwhelmed.

Depending on the solution you choose, you will have to consider citizen data scientist training. While there are citizen data scientist certification courses, if you choose the right augmented analytics solution you are not likely to need this type of training but, rather a simple introduction that will explain the new role, how to work with and collaborate with data scientists and IT and how to use the augmented analytics solution to get the information the business user needs in a way that is meaningful to them.

‘One of the most important aspects of any new, large scale initiative, is preparation and when it comes to the Citizen Data Scientist approach, preparation is equally important.’

For a detailed discussion of Citizen Data Scientists and related topics, read our article: ‘What Is A Citizen Data Scientist, What Is Their Role, What Are The Benefits Of Citizen Data Scientists…And More!’

Contact Us to find out how augmented analytics Technology can support your enterprise, and ensure analytical clarity and results. Discover the next level of Self-Serve Analytics and explore online Citizen Data Scientist Training and the features and modules of a seamless, sophisticated, easy-to-use augmented analytics solution to see how your business can use analytics to achieve its goals. Explore our complementary articles on Citizen Data Scientists: ‘The Importance And Benefits Of A Citizen Data Scientist Initiative,’ ‘What Is A Citizen Data Scientist And How Has Their Role Changed?’ ‘Engage A Skilled IT Partner And Achieve Citizen Data Scientist Success,’ and ‘What Is A Citizen Data Scientist, What Is Their Role, What Are The Benefits Of Citizen Data Scientists…And More!’

Original Post: Plan Carefully for a Citizen Data Scientist Program!

Citizen Data Scientists Can Partner With Data Scientists!

author_img
by |
August 6, 2024

A Citizen Data Scientist Initiative Can Optimize Data Scientists and Encourage a Data-Driven Culture!

According to some estimates, the average salary of a Data Scientist in the United States is over $150,000 per year. If your business wishes to accommodate a ‘data-first’ strategy to improve metrics and measurable success and avoid guesswork and strategies that are based on opinion rather than fact, it can either employ a team of expensive professionals, or it can take a different approach.

‘Citizen Data Scientists can use their knowledge of a business sector, industry, function or market to drive questions and develop reports and presentations to illustrate issues, identify problems and find opportunities for growth and competitive positioning, and share this data (and the search and analytical techniques) with other users.’

Citizen Data Scientists are business users who have a place on your team and are hired because of their professional and career experience in a particular industry, business function or discipline. When they are given access to data analytics, they can merge their knowledge of an industry, e.g., research, healthcare, law, finance, sales, supply chain, production, construction etc., with data integrated from databases, best-of-breed software programs, ERP, SCM, HRM and other systems and use sophisticated analytical tools in an easy-to-use, intuitive environment to gather and analyze data and produce insightful, concise results that are meaningful to their role.

Leverage Citizen Data Scientists to Augmented Data Scientist Teams

Depending on the size, market and industry of your business, you may choose to augment your staff with one or more data scientists to refine results produced by Citizen Data Scientists on a day-to-day basis. So, if a power user or business users discovers a challenge or an opportunity and your management team wishes to further explore the issue to understand its strategic or operational value, a Data Scientist can take the predictive model or other analytical report produced by a Citizen Data Scientist and refine the results for executive review.

Whether you choose to employ the services of a Data Scientist, provide business analysts or IT professionals to support your business users, you can create a comprehensive foundation for analytics across your organization.

By democratizing data analytics you can achieve many benefits, including:

  • Improved Data Literacy Across the Enterprise
  • Improved Productivity of Data Scientists, IT and Business Analysts (who can spend time on strategic initiatives rather than producing daily reports)
  • Optimized Return on Investment (ROI) and Total Cost of Ownership (TCO) for all software and systems
  • Fact-Based Decisions and Metrics-Driven Strategies, Goals and Objectives
  • Team Member Career Advancement
  • Optimization of Resources and Improved Team Productivity

A comprehensive self-serve augmented analytics solution will include Modern Business Intelligence (BI) and Reporting with Key Performance Indicators (KPIs), Self-Serve Data Preparation, Assisted Predictive Modeling, and Smart Data Visualization with auto-suggestions to drive the analytical techniques and illustration of data based on data type, volume, etc., and other tools like Embedded BI, Mobile BI, Key Influencer Analytics, Sentiment Analysis, and Anomaly Alerts and Monitoring.

With these tools, the Citizen Data Scientist can leverage Natural Language Processing (NLP) and search analytics with machine learning to ask questions using simple human queries and receive insightful answers. They can use their knowledge of a business sector, industry, function or market to drive questions and develop reports and presentations to illustrate issues, identify problems and find opportunities for growth and competitive positioning, and share this data (and the search and analytical techniques) with other users.

Citizen Data Scientists can predict customer responses to new product features, and to new marketing campaigns, analyze the likelihood of fraud or risk, identify supply chain issues, etc. These tools can also help the organization to foster collaboration and data sharing and encourage business users to innovate, create and explore opportunities using data-driven, factual information.

‘When Citizen Data Scientists are given access to data analytics, they can merge their knowledge of an industry, e.g., research, healthcare, law, finance, sales, supply chain, production, construction etc., with data integrated from databases, best-of-breed software programs, ERP, SCM, HRM and other systems and use sophisticated analytical tools in an easy-to-use, intuitive environment to gather and analyze data and produce insightful, concise results that are meaningful to their role.’

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 : Leverage Citizen Data Scientists to Augmented Data Scientist Teams!

Give Your Business Users Assisted Predictive Analytics!

author_img
by |
July 30, 2024

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!

Augmented Analytics Provides Benefits to Data Scientists!

author_img
by |
May 17, 2024

When an enterprise undertakes an Augmented Analytics project, it is typically doing so because it wishes to initiate data democratization, improve data literacy among its team members and create Citizen Data Scientists. The organization looks for a solution that is easy enough for its business users and intuitive enough to produce clear results; one that also provides sophisticated functionality and features and will produce a suitable Return on Investment (ROI) and Total Cost of Ownership (TCO).

Continue reading “Augmented Analytics Provides Benefits to Data Scientists!”

White Paper – Enabling Business Optimization and Expense Reduction Through the Use of Augmented Analytics

author_img
by |
May 9, 2024
White Paper – Remote and Hybrid Technology Outsourcing Models Are Now Mainstream and the Future is Bright!

white-paper-enabling-business-optimization-and-expense-reduction-through-the-use-of-augmented-analytics

No matter the reason or the goal, when an enterprise chooses the right Augmented Analytics solution and carefully plans for and executes its implementation, it can optimize business results, reduce expenses and improve its market position, customer satisfaction and user adoption, and it is key to transforming business users to Citizen Data Scientists to improve results and team skills. Here, we examine the benefits of Augmented Analytics and how to plan and successfully execute an Augmented Analytics initiative.

Download White Paper

AI In Analytics: Today and Tomorrow!

author_img
by |
April 19, 2024

Nothing…and I DO mean NOTHING…is more prominent in technology buzz today than Artificial Intelligence (AI). The use of Generative AI, LLM and products such as ChatGPT capabilities has been applied to all kinds of industries, from publishing and research to targeted marketing and healthcare. Gartner recently estimated that the market for AI software will be nearly $134.8 billion, with the market growing by 31.1% in next several years. In a recent survey of C-suite executives, 80% of said they believe AI will transform their organizations, and 64% said it is the most transformational technology in a generation.

(more…) "AI In Analytics: Today and Tomorrow!"