Tag: Citizen Data Scientist

Augmented Analytics Must Provide Data Quality and Insight!

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April 25, 2024

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.

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AI In Analytics: Today and Tomorrow!

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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!"

Key Influencer Analytics Tells You How to Succeed!

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March 19, 2024

Use Key Influencer Analytics to Understand What Factors Impact Success!

Suppose you are trying to understand why a marketing campaign is failing, or what factors cause your customers to buy your services again. What if you need to know whether the color of a product affects the number of units sold in a particular country or area of a country? There are so many variables and components that can affect business success, and understanding the relationship among all the factors of success can seem like a guessing game.

When you are faced with this quandary, it is wise to use analytics to take the guesswork out of the equation. But how do you begin to analyze all the factors at play?

‘Can an augmented analytics tools tell you what algorithm or analytical technique to use? Can it help you understand the relationships of various factors and issues and determine what changes will help you improve the revenue for a product, or help you create a new service package?’

Statistical and analytical experts will tell you that there are three primary factors that can help you decide on the metrics to use for your analysis:

  • The type of data you want to analyze – Understanding the data type can help you decide whether you need to consider a binary approach or look at categories, etc.
  • The character of the data you want to analyze – Are you looking at product attributes, a specific threshold or data range, etc.
  • What you want to accomplish with your analysis – Do you want to identify trends or patterns or are you trying to understand the relationships among the various factors and which factors affect success?
Key Influencer Analytics Helps You Understand Success

…and there is one more critical issue you must consider. Namely, who is doing the analysis? If you want to democratize data and improve data literacy across your enterprise, you will want your business users to understand and use analytical tools. But your team members are not statisticians or data scientists. So, they will need easy-to-use augmented analytics tools.

But can an augmented analytics tools tell you what algorithm or analytical technique to use? Can it help you understand the relationships of various factors and issues and determine what changes will help you improve the revenue for a product, or help you create a new service package?

One of the most frustrating tasks a business user has in analytics is finding and gathering the right data for analysis and ensuring that all factors, variables and data that may affect the outcome of the analysis is included. Depending on the size of the dataset a user selects, there may be hundreds or thousands of variables, and business users often find it difficult to identify the rights ones. Yet without the ability to identify the right variables, the business is likely to measure and attend to the wrong things.

That’s where Key Influencer Analytics comes into play! This approach puts the power and clarity of targeted analytics in the hands of business users and support Citizen Data Scientist initiatives and the critical goals of Data Literacy across the organization.

The user can simply point to the dataset they want to analyze and the system will identify the target and the influencers or predictors that will affect the target, along with its impact and it provides crucial metrics such as mean, outliers, and others and identifies relationship and distribution among variables. The system will auto-suggest relationships and present distribution and impact using the most appropriate visualization.

Users enjoy interactive features that allow them to see and explore other combinations and impacts and can select target and predictors, and use them for models, reports or KPIs. Key Influencer Analytics empowers every business user and allows them quickly select and target data to achieve results without the assistance of a data scientist, IT professional or analyst.

Key Influencer Analytics will:

  • Identify feature importance based on machine learning algorithms
  • Interpret insights in simple language
  • Measure statistics
  • Reveal influencers with impact on the target
  • Auto recommend influencers
  • Identify data relationships with interactive visualization

With these tools, business users can identify what matters most within the data, and how the various factors and relationships impact success, and they can understand the interdependence of variables and leverage auto-suggestions and machine learning functionality to gain insight. Users can also leverage the features within the tool to consider various combinations and the impact of those combinations on the success of the project, product or plan.

‘There are so many variables and components that can affect business success, and understanding the relationship among all the factors of success can seem like a guessing game.’

Find out how Key Influencer Analytics can benefit your business users and support Citizen Data Scientists, and how it can provide an advantage to your data scientists, business analysts and IT team members.

Original Post: Key Influencer Analytics Tells You How to Succeed!

Augmented Analytics with Auto Insights Support Business Users!

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March 7, 2024

Augmented Analytics with ALL Gartner Classified Essential Components AND Auto Insights Too!

Gartner classifies essential augmented analytical components and technologies as follows:

  • Machine learning
  • Natural Language generation and natural language processing
  • Automation

‘Combine the three essential components specified by Gartner to create a comprehensive augmented analytics solution with refined auto insights and clear, concise results, the enterprise and its business users can perform complex data analytics and share analysis across the organization in a self-serve, mobile environment.’

While none of these is considered ‘new’ in the market today, the combination of essential components and the leveraging of new technologies and features is key to keeping augmented analytics fresh and usable for the average business user.

One such feature that users will look to for quick results and clear, concise decision support is the concept of auto insights.

Auto Insights Adds Clarity and Ease-of-Use to Augmented Analytics

Search Analytics is evolving at a rapid pace, and the concept of auto insights builds on the foundation of assisted predictive modeling and Clickless Analytics features, taking natural language processing (NLP) search analytics and predictive modeling to the next level.

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.

Using this approach, business users will no longer have to select data columns or analysis techniques such as classification or clustering. Instead, the user will simply select the dataset to be analyzed. That’s it!. The system interprets the dataset, selects important columns of data, analyzes type and variety and other parameters and then uses intelligent machine learning to automatically apply the best algorithm and analytical technique and provide data insights.

Users can easily understand data and apply correlation, classification, regression, or forecasting, or other appropriate technique(s) based on the data the user wishes to analyze. Results are displayed using visualization types that provide the best fit for the data, and the interpretation is presented in simple natural language. This seamless, intuitive process enables business users to quickly and easily select and analyze data without guesswork or advanced skills.

By combining the three essential components specified by Gartner to create a comprehensive augmented analytics solution with refined insights and clear, concise results, the enterprise and its business users can perform complex data analytics and share analysis across the organization in a self-serve, mobile environment.

This approach provides support for sophisticated, advanced analytics and smart data visualization to automate the analysis process, so business users can simply point to a dataset and let the system do the rest.

‘The combination of essential components and the leveraging of new technologies and features is key to keeping augmented analytics fresh and usable for the average business user.’

Find out how Smarten Auto Insights can help your team and your organization. Leverage the essential components of Augmented Analytics, as defined by Gartner, and provide seamless, easy-to-use, sophisticated features and functionality to support your business users and transition your team members to Citizen Data Scientists.

Original Post: Augmented Analytics with Auto Insights Support Business Users!

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!

Give Your Business Users Mobile BI to Ensure Success!

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February 7, 2024

Why Should My Enterprise Provide Mobile Business Intelligence (BI) Tools to Business Users?

Many businesses are beginning to see and leverage the value of business intelligence and augmented analytics within the organization to engender data democratization, improve data literacy and collaboration and improve results. In a competitive global and local business environment, this move toward analytics for all is a positive thing.

If your business is considering BI tools or augmented analytics, or if you have already implemented these tools within the enterprise, there is one more question to answer.

Does your organization provide Mobile BI to its business users? If it does not, you are missing out on a crucial opportunity and a critical business advantage.

‘Mobile augmented analytics can benefit your business users and help to transform them into Citizen Data Scientists.’

When considering a Mobile BI app, it is important to verify ease of access and availability of data on the road and anywhere your team may be working, and to ensure that your team has tools that are easy-to-use and will enable user adoption.

Can My Business Users Benefit from Mobile BI?

If you select the right mobile business intelligence (BI) app, you can enjoy the following benefits:

  • A native app, with seamless user interface for a great user experience (Ux). Available for iOS and Android
  • Extends the office environment. Allows swift analysis and decisions from anywhere
  • Encourages user adoption and provides support for BI investments and data democratization
  • Access rights are defined on the server so security and privacy is ensured at all levels
  • Supported by a server that is hosted anywhere within IT infrastructure –on premises, public or private cloud
  • Business Users will have access to dashboards, reports, Clickless Analytics – Google-type Natural Language Processing (NLP) Search functionality
  • Start-up is easy, within a few minutes and support is readily available

The right Mobile BI App should include the following components and features:

  • Provide access to Dashboards, Graphs, KPIs, PDF reports, and Clickless Analytics – NLP Search – all from within the mobile app.
  • Users login with an enterprise login, browse and search objects, and access objects for interactive analysis with access to ‘my favorites’ for quick navigation, i.e., objects marked as favorites, and recently used objects.
  • Download Smarten objects via PDF, XLS, and other file formats and share via WhatsApp, email or other sharing app loaded on their device.
  • Natural Language Processing (NLP) search, where users can query a dataset with a Google-type interface where a user can compose a question using natural English language and receive answers using visualization that provides the best-fit for the user inquiry. With natural language-processing-based search capability, users do not need to scroll through menus and navigation. Enter a search query in natural language and the system will translate the query, and return the results in natural language in an appropriate form, such as visualization, tables, numbers or descriptions.
  • No requirement to redesign or customize dashboards and reports to accommodate a mobile device. Dashboards and Reports are displayed and optimized for the best user experience on the mobile device.
  • Licensing fees are affordable and implementation is easy and fast.

‘When considering a Mobile BI app, it is important to verify ease of access and availability of data on the road and anywhere your team may be working, and to ensure that your team has tools that are easy-to-use and will enable user adoption.’

Find out how Mobile BI and mobile augmented analytics can benefit your business users and help to transform them into Citizen Data Scientists, and how it can provide an advantage to your data scientists, business analysts and IT team members.

Original Post: Give Your Business Users Mobile BI to Ensure Success!

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.

Continue reading “Should I Start a Citizen Data Scientist Program?”

The Efficacy of Citizen Data Scientists is Proven!

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October 13, 2022

Listen to the Experts: Citizen Data Scientist Results are Real!

Gartner has predicted that, ‘a scarcity of data scientists will no longer hinder the adoption of data science and machine learning in organizations.’ As businesses embrace the concept of transforming business users to Citizen Data Scientists, the Gartner prediction takes on a very practical application and enterprises try to sort through the roles of data scientists, business analysts and Citizen Data Scientists.

‘You can be a subject matter expert, or a professional trained in a very specific business function or industry and you can combine this expertise with augmented analytics to achieve your goals.’

Those at the top of major corporations, with experience in managing the reality of the data science landscape, are now realizing that they can create a collaborative environment that includes those who have data science and statistical experience, as well as those who have professional experience that is brought to bear for operational and strategy decisions by combining industry and domain knowledge with intuitive data tools and solutions.

In a recent CDOTrends Article, experts describe a data analytical environment that includes economists, engineers, data scientists and others from varied disciplines. In another publication in Fortune Magazine, experts talk about the very real evolution of data science and the fact that professionals at all levels will need to use, and WILL be using, data and analytics.

The Results Are In: Citizen Data Scientists ARE Beneficial

These articles point out the fact that Gartner predictions are now a reality, and that data science is proliferating across organizations of all sizes in all industries. Foundational data science skills are important but, as Gartner has predicted, the sophisticated, professional data scientist training is not required for business users to participate in, and benefit from, data analytics. Augmented analytics, designed for use by business users, provide tools that are easy enough for all users, and allow for natural language processing (NLP) and search analytics in an environment where users only have to ask a question, and can then allow a system to provide the context-oriented response they need to gain insight into an issue.

You can be a subject matter expert, or a professional trained in a very specific business function or industry, and you can combine this expertise with augmented analytics to achieve your goals. Data Scientists can then focus on strategic initiatives where analytics must be 100% accurate. When a business provides support for business users to transition into Citizen Data Scientists, the tools allow business users to leverage sophisticated techniques and to become more data literate and comfortable with analytics as part of their day-to-day workflow and business processes.

All of this is a long way of saying that Citizen Data Scientists are a reality today, and that the evidence of efficacy and effectiveness exists in many organizations today.

‘Combining professional experience to make operational and strategy decisions, and a user’s industry and domain knowledge with intuitive data tools and solutions is a powerful benefit to the enterprise.’

As we gain experience with the new reality of distributed data science, we hear from senior executives and experts who have seen the good and the bad of the evolution. And, the experts tell us that the most important trait of successful data analysis is curiosity. Citizen Data Scientists can use their experience in their role to ask the right questions and allow the new generation of augmented analytics solutions to provide the answers, without coding or sophisticated data science skills. Business users can easily understand what the data is saying in layman’s terms and translate complex issues into insight that is easy to understand.

Transforming business users into Citizen Data Scientists, provides advantages to the organization, to the business users and to data scientists. Today, businesses can explore a FREE Online Citizen Data Scientist Course, and the right augmented analytics solution, and organizational planning, to build a solid foundation and business user confidence. The business should also consider engaging an IT consulting partner with knowledge of the augmented analytics market, and a solution and support services to provide the guidance and Products And Services your business will need to succeed.

Original Post : The Efficacy of Citizen Data Scientists is Proven!

Imagine How Citizen Data Scientists Can Help Your Business!

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September 13, 2022

Imagining the Impact of Citizen Data Scientists!

Technology research and analysis firm, Gartner, coined the term, ‘analytic process automation.’ This process ‘converges data science, analytic and process automation into a single platform—which helps companies automate and integrate the way data and business processes come together. Companies can also make data more actionable across the organization.’

‘By providing augmented analytics tools to all business users, with appropriate access and security, each team member has seamless, clear insight into data and can apply analytics to support their roles and responsibilities.’

When an enterprise undertakes a Citizen Data Scientist initiative, it is striving to do just that. In other words, the business wants to make data more actionable across the organization.

In this article, we review the possibilities of the Citizen Data Scientist environment in an effort to help your organization imagine the new business landscape.

Citizen Data Scientists Achieve More Results

Power Users and Champions

With the right augmented analytics tools, designed specifically for business users, team members can leverage analytics, smart data visualization, self-serve data prep and predictive analytics and all of the sophisticated analytical techniques they will need to make fact-based decisions and recommendations. Those team members who are curious about analytics and comfortable sharing knowledge of these technology tools will become power users and champion the democratization of data and data literacy throughout the organization. This cultural shift will take team members out of the ‘wait and see’ environment and avoid guesswork and opinion, and the delays and data gaps that occur when a business user must depend on IT or on data scientists to get detailed, concise reports.

Business Process Streamlining

By enabling personalized dashboards and pushing alerts and reports, businesses processes can be streamlined and users can create dependable processes and actionable data without wading through restrictive reports, or trying to interpret information coming from disparate sources and staff members. Key Performance Indicators (KPIs) provide streamlined, data-based metrics and measurements and keep the team on track.

Collaboration

Augmented Analytics solutions that support business users encourage collaboration and data sharing and allow users to test theories and hypothesize, sharing the results of their research and creating business use cases that can be applied to real-world issues, challenges and opportunities.

Goals and Objectives

By providing augmented analytics tools to all business users, with appropriate access and security, each team member has seamless, clear insight into data and can apply analytics to support their roles and responsibilities. Actions and tasks can be tied to appropriate metrics and to specific goals and objectives to ensure that every team member is working to achieve business goals in a timely, accurate fashion.

‘When an enterprise undertakes a Citizen Data Scientist initiative, it is striving to make data more actionable across the organization.’

Transforming business users into Citizen Data Scientists, provides advantages to the organization, to the business users and to data scientists. With appropriate Citizen Data Scientist Training, the right augmented analytics solution, and organizational planning, the business can provide a solid foundation and build business user confidence by providing an introduction and fundamental information on Predictive Analytics and other tools these users will employ. The business should also consider engaging an IT consulting partner with knowledge of the augmented analytics market, and a solution and support services to provide the guidance and Products And Services your business will need to succeed.

Original Post : Imagine How Citizen Data Scientists Can Help Your Business!

Context-Driven Natural Language Processing (NLP) Beats ‘Dumb’ NLP Every Time!

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August 24, 2022

If you are an avid reader of technical research or industry journals, you probably know about Natural Language Processing or NLP. If you don’t know about it, you certainly use it every day – whether you know it or not! When you search using Google, you are using natural language and that makes it easier for you to develop a question and get an answer. Ask a question and get an answer. It’s that simple!

But, when it comes to analytics, NLP is typically much more restrictive. Talk all you want about machine learning and natural language processing but the boundaries and restrictions placed on these concepts in a typical analytical solution do not make it as easy as business users might like.

Remember that your business team members are also consumers outside the walls of the office and they use and appreciate the ease of Google searches. Here, a consumer might ask, ‘how many ounces in a pound’, or ‘what is the tallest building in the world’, and they get an immediate answer. THAT is what they want in analytics as well and if you don’t give it to them, they are unlikely to adopt the analytical tools you invested in or to achieve the results you wanted for optimizing resources, improving productivity and, most importantly, engaging in fact-based decision making that will improve the business bottom line.

So, what, if anything can one do about the disconnect between the ease of use of analytics and the typical NLP solution? To answer this question, we first need to understand the difference between standard natural language processing in analytics (AKA Dumb NLP) and context-driven searching using natural language processing (AKA Intuitive NLP).

Context-Driven Natural Language Processing (NLP) Beats ‘Dumb’ NLP Every Time

Context-driven natural language processing allows people to think and communicate like people – not like machines! It is intuitive and ‘smart’ and goes far beyond ‘dumb’ NLP.

Dumb NLP: The use of NLP in analytics provides the basic foundation to get a user into the details of the data and allow them to choose and filter using columns and filters. It recognizes the data in the column or field but not the context. Much like a text to speech solution, it can read, translate and present the data but it has no real understanding of what the data means. Users often get frustrated when they try to use these tools because they have to wade through the choice of columns, click on menus and sift through scripts and when the NLP query results are presented, they may discover that they did not get what they wanted because they omitted or included some inappropriate data.

Intuitive NLP: Context-driven natural language processing allows the user to think of a question and ask that question in a way that supports human thought, and natural communication. Context-driven NLP ‘understands’ and interprets the question and the user intention so, for example, if a user wants to find sales results for a product sold during the ‘Thanksgiving’ season, they do not have to know the date for a particular year or years. They can simply ask the question. ‘How many donuts were sold in Scottsdale, Arizona during Thanksgiving 2019 and 2018? The system will understand the question and interpret it to provide the right information.

Much like your best friend can understand your intent and respond to a question without your being concise or detailed, context-driven NLP can handle the subtleties and the context without the need for excruciating detail and restrictive programming or scripting.

Ask, ‘What was the best day of bakery sales in Tucson Az last year?’, and the system will know that, a) the ‘best day’ means best day of sales for you, that b) bakery sales means all items that fall within the bakery category in your product portfolio, such as cake, brownies, croissants, cookies, bread etc., c) that Az means Arizona and that d) last year was 2019. Just ask the question…and you will get an answer. It’s that simple.

Context-driven, intuitive NLP provides many opportunities to ask questions and handles many concepts, including,

Synonyms, Phonetics and Abbreviations – Enter question and the system will recognize and process information correcting for spelling errors, abbreviations and related words.

Geography, Places and Persons – Enter a question and allow the system to identify a person or place automatically, and give the answer in context of person or geo location.

Time Series – Enter a question and receive results based on absolute time, or on a range or relative time period.

Rank and Polarity – Enter a question and receive results based on a determination of ‘higher’ or ‘lower’ results.

Aggregation – Enter a question to understand results for averages, minimum, maximum, first, last, sum, counts, etc.

Comparison – Explore how sales or other factors compare from one region, year or variable to another.

Context-driven natural language processing allows people to think and communicate like people – not like machines! It is intuitive and ‘smart’ and goes far beyond ‘dumb’ NLP by offering tools that users will want to leverage and interacting with users in a way that is meaningful to them. Your business users don’t need have to use or understand sophisticated skills to create a query or ask a question. They don’t have to wade through five or ten steps to create a query. With context-driven NLP, users just have to think of a question and type that question and they will get the answers they need.

Make your business more productive, optimize resources, empower your team members and allow them to make confident, fact-based decisions and to solve problems and get the information they need to do their job – without stress or time-consuming training or procedures! THAT is the difference between using ‘dumb’ NLP and using intuitive (context-driven) NLP in analytics.

Original Post : Context-Driven Natural Language Processing (NLP) Beats ‘Dumb’ NLP Every Time!