Why Should My Business Adopt Embedded BI and Analytics?
There are many reasons to consider adding embedded BI to your enterprise technology landscape. When you are making a critical business decision, one of the factors you probably include is how your competitors and other businesses are addressing the problems you are trying to solve. When making a decision about Embedded BI consider these survey results. Businesses that are currently using embedded BI within their enterprise, report the following:
Add Mobile BI for Your Team and Improve Access, Analytics and Business Decisions!
Recent surveys reveal that the mobile BI market is growing by leaps and bounds. Of those surveyed, over 35% of companies said that mobile BI is in use among their business users. While some businesses have yet to adopt BI tools or augmented analytics for their business users, many have done so, and are now in the process of adding mobile BI to the set of tools available to users. There is no doubt that the COVID pandemic affected this strategy, since many businesses are now embracing a full-time or a hybrid remote work environment that requires team members to have access to tools from wherever they are working.
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?
…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.
If you are an IT professional, a business manager or an executive, you have probably been following the progress of the Citizen Data Scientist movement. For a number of years, Gartner and other technology research and analysis firms have predicted and monitored the growth of this phenomenon.
In fact, Gartner predicted that, ‘…40% of data science tasks will be automated, resulting in increased productivity and broader usage by citizen data scientists.’
So, how is it going? It’s actually going quite well.
However, it is worth noting that some businesses have not had the success they expected when implementing a Citizen Data Scientist approach. One of the primary reasons for falling short of results is to set inappropriate expectations regarding the role of Citizen Data Scientists vs. Data Scientists within the organization.
As the Citizen Data Scientist approach gained momentum, businesses seemed to develop an expectation that Citizen Data Scientists could replace Data Scientists. Nothing could be further from the truth. Augmented Analytics and Citizen Data Scientists are not meant to replace refined data modeling or the role of Data Scientists, but rather can supplement and support analytics across the enterprise. The enterprise should not discount the value of strategic data analytics and its place in the organization but rather should see augmented analytics and Citizen Data Scientists as a way to drive fact-based decisions and provide clarity and data-driven actions across the enterprise.
The fact is that there is a place for Citizen Data Scientists within your business, AND a place for Data Scientists and the strategic use of their skills.
If you want your Citizen Data Scientist initiative to succeed, and you wish to achieve data democratization and data literacy, you must understand how augmented analytics should be used to support business users and organizational objectives. So, let’s dive in and explore this issue further.
AUGMENTED ANALYTICS SOLUTIONS
When selecting an augmented analytics solution, your enterprise must choose tools that are designed specifically for business users with average technology and analytical skills. Easy-to-use, intuitive tools will ensure user adoption. If you choose business intelligence or advanced analytics tools that are meant to data scientists, IT professionals or business analysts, you are setting your team up to fail. These tools are focused on the needs of Data Scientists. The tools are powerful and can produce undeniable value in the right hands, but they are not designed for your business professionals. To use these tools, users must manually gather and prepare data, scrubbing, cleaning, etc., and then write complex queries and use complicated algorithms and analytical techniques. Users must be expert in R programming or in Python or other scripting and programming languages. In short, this kind of software, app or solution is not for the feint of heart, and it’s certainly not suitable for a Citizen Data Scientist.
The right business user solution is an augmented analytics should be designed with all the tools a business user needs to get swift, dependable results.
Self-Serve Data Preparation
Assisted Predictive Modeling
Smart Data Visualization
Machine Learning and Natural Language Processing (NLP)
Clickless Search Analytics
EXPECTATIONS AND RESULTS
Once you have chosen the right augmented analytics solution, you must establish appropriate expectations.
MANAGERS AND EXECUTIVES SHOULD NOT EXPECT CITIZEN DATA SCIENTISTS TO BE DATA SCIENTISTS
That is not the purpose of this strategy. The purpose of a Citizen Data Scientist approach is to give your team members tools that will allow them to discover trends and patterns, and to gain insight into what is working and what is not working in their current process, workflow and in their day-to-day activities. If and when an issue is identified that will require adapting a strategy or a major goal or objective, the enterprise must have a process in place that will allow a team member to refer her/his research to a Data Scientist, IT team member or other analytical professional, where the initial analysis will be refined and studied for use in strategic goals. When a Citizen Data Scientist uses augmented analytics, they should not be expected to perform complex modeling or to establish predictive models that will be rolled out in production mode or dictate a new strategy.
CITIZEN DATA SCIENTISTS SHOULD FOCUS ON HYPOTHESIS AND PROTOTYPING
If a business user/Citizen Data Scientist discovers an issue or an opportunity, that user can explore the issue, look for relationships among the variables and factors that affect success and failure, develop an understanding of the challenge or the possibilities for product bundling, changing a marketing campaign, etc., and then share and collaborate with the team to further analyze and discuss the issues. It is this day-to-day access to analytics and clear data that will allow business users to make fact-based decisions and to build an understanding of data and analytics and how the information contained in data repositories and software systems can be integrated and analyzed to gain more clarity and to provide real metrics and measurements, so decisions are based on facts, rather than guesswork and opinion.
Role – Day-to-day business decisions, team collaboration and data sharing.
Benefits – Improved team collaboration, improved data literacy and perspective, improved business agility, timely decisions.
DATA SCIENTISTS SHOULD FOCUS ON STRATEGIC GOALS AND DATA REFINEMENT
Most organizations cannot afford a team of Data Scientists and, even if they could, they do not want those professionals pulled away from crucial, strategic focus by day-to-day requests and projects that have short-term outcomes and importance. Rather than trying to replace Data Scientists within the business, the enterprise can optimize their time and reduce the need to hire more resources, by improving focus and enabling a workflow that allows them to concentrate on those areas that will reap the most benefit to the organization.
Role – Analyze and refine data for 100% accuracy and strategic use, act as expert, statistical expert.
Benefits – Focus on strategic issues with fewer day-to-day requests, collaborate on projects that require data refinement for 100% accuracy, focus on mature modeling requirements.
When an organization sets out to leverage the Citizen Data Scientist approach, it can ensure success by taking the time to plan appropriately AND by establishing appropriate expectations for how and when business users will engage in analytics and the results they can and should produce. When an organization understands the true meaning and purpose of the Citizen Data Scientist role, it can incorporate this strategy and align business users and Data Scientists to achieve greater collaboration and synergy.
Be sure you choose a vendor with comprehensive augmented analytics features and functionality designed specifically for business users, to support the transition of your business users to Citizen Data Scientists and ensure that your project will succeed. Contact Us to find out how we can help you plan and achieve your goals. It really IS possible!
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.
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.
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!
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:
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.
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.
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.
Support Your Team and Achieve Business Results with a Mobile BI Solution!
Gone are the days when every employee in your enterprise was tied to a desk inside the walls of your office building. Today’s team members are working remote, or visiting clients, or on the road, or perhaps they are in the office in a staff meeting and in need of crucial information to make a decision. Whatever the case, your team needs flexible, mobile solutions to do their jobs in today’s high-stakes, competitive environment, and mobile BI is definitely among the solutions they need.
‘If you want to support your business user team, explore mobile augmented analytics and mobile BI, you can add powerful functionality and access for your business users with out-of-the-box Mobile BI.’
Mobile BI solutions provide data for analysis on mobile devices to support objective, fact-based decision-making improve overall business performance.
According to Mordor Intelligence, ‘The growth in the adoption of mobile BI can be attributed to numerous factors, such as the growing adoption of data analytics, an increase in mobile data generation, proliferation of mobile devices and apps, and the improved efficiency of BI tools.’
There are many benefits to creating a Mobile BI environment:
Your users can leverage a native app, with a seamless user interface for a great user experience (Ux)
The enterprise can extend the office environment, allowing for swift analysis and decisions from anywhere and improving productivity
Mobile BI will encourage user adoption and provide support for BI investments and data democratization and improved data literacy
The organization can ensure data security with access rights defined on the server, so security and privacy is ensured at all levels
The mobile BI app is supported from anywhere within IT infrastructure –on premises, public or private cloud
Business Users have access to dashboards, reports, Clickless Analytics – Google-type Natural Language Processing (NLP) Search functionality
Whether you have an existing business intelligence or augmented analytics platform that you wish to upgrade or change, or you are exploring the potential of augmented analytics for your business user team and want to implement a Mobile BI environment to support your team within and outside the office, you can enjoy the benefits of this approach, with a cost-effective solution that is easy to implement and requires minimum training and roll-out time.
‘Your team needs flexible, mobile solutions to do their jobs in today’s high-stakes, competitive environment, and mobile BI is definitely among the solutions they need.’
If you want to support your business user team, explore Smarten Mobile Augmented Analytics And Mobile BI, you can add powerful functionality and access for your business users with out-of-the-box Mobile BI and advanced analytics for every team member. For more information on Mobile BI and Augmented Analytics, read our article, ‘Understanding The Truth About Mobile BI.’
The Client is India’s largest omni-channel jewelry brand, and is recognized and renowned by India consumers. The Client has 165 retail stores in 66+ cities across India, as well as a thriving jewelry eCommerce presence online. Its product line includes rings, earrings, pendants, necklaces, chains, bangles, bracelets, mangalsutra, and nose pins, as well as 22k (916) and 24k (995) gold coins with certification and BIS Hallmark stamp guarantee. The Client customer base is growing rapidly, and to attract and retain customers, the business provides new designs and uses a mobile application to bridge the gap between brick-and-mortar stores and the virtual world. The mobile app provides a Virtual Try-On feature that allows customers to ‘try on’ jewelry and designs using a virtual reflection and image.
Consider the Benefits of Low Code No Code for Augmented Analytics!
Low code/no code (LCNC) application development is regarded as an innovative step in the future of software development. With its reusable components, drag-and-drop features, visual creation process, and emphasis on digital democracy, opting for low code/no code application development becomes essential.
Simply put, Low Code software development allows development of enterprise applications with a minimal need for coding. Low code development platforms provide users with a suite of tools, custom code components, and boilerplate scripts. No Code software development requires minimal programming skills to quickly build an application. This explanation provides a simple understanding of both approaches and, for the purpose of this article, we will not dive into the details.
Statista predicts that, ‘… the global low-code platform market is forecast at approximately sixty-five (65) billion USD within the next several years.’ This market and the popularity of this approach is based on the need to simplify and speed the prototyping and planning process and to provide simple components and building blocks so that complex development projects and software can be upgraded and improved quickly with new features and functionality added dependably, and high-performance ensured.
‘Remember that choosing the right business intelligence (BI) and augmented analytics solution, built upon the right foundation will dictate user adoption, return on investment (ROI) and total cost of ownership (TCO) as well as the overall success of your business intelligence project.’
When low-code or no-code development is utilized in augmented analytics, it can provide an environment where upgrades can be accomplished rapidly, ensuring that the features, functionality and performance of the augmented analytics app or software is relevant, leverages the right new technologies and techniques and allows users to enjoy easy-to-use, high-performance features without a lot of training or implementation cost or time.
At the organizational level, the low code, no code approach encourages user empowerment and user adoption. It enables data sharing and allows the enterprise to produce fast, dependable insights and improve the value of business analysis across the enterprise, democratizing the use of advanced analytics.
Remember that choosing the right business intelligence (BI) and augmented analytics solution, built upon the right foundation will dictate user adoption, return on investment (ROI) and total cost of ownership (TCO) as well as the overall success of your business intelligence project. Your vendor and software app must be able to support rapid market and technology change and allow you to grow, expand and adapt quickly. Building on a low-code, no-code foundation allows your software partner to quickly and easily support the needs of the market and provide you with the tools you need to improve results.
‘When low-code or no-code development is utilized in augmented analytics, it can provide features, functionality and performance using the right new technologies and techniques.’
Find out how the Smarten Low-Code, No-Code approach to development can help your team and your organization. Integrate artificial intelligence (AI) and machine learning within your analytical environment, and leverage sophisticated analytics in an easy-to-use user interface to improve performance and user adoption. Explore the additional benefits of the Smarten Cloud software-as-a-service (SaaS) product with its low-code, no-code foundation and seamless functionality.
You have decided that your business can benefit from an analytics solution. Now, it is time to convince your executive team, your managers and your users. If you are to gain approval for your initiative, you must take the right approach.
In this article, we discuss some of the primary factors you must consider to build and present your initiative to the various audiences within your organization.
A four-year study of businesses implementing analytics solutions found the following:
Less than 50% of the businesses reported measurable results
Only one third of the businesses met their objectives for user adoption
77% said that user adoption was a challenge
Only 20% reported that analytics insights provided positive business outcomes
Before you give up on your initiative, consider this: most software projects fail because of poor planning and execution. So, if you can plan appropriately, you will be way ahead of the game. Here are a few factors you will need to include in your review and planning process.
IT Team – Be sure you include your IT team in your planning. You will need a comprehensive understanding of your existing technology, hardware, network and devices and you will need the help of your IT team to assist you in planning roll-out, estimating the cost of new technology to implement your plan, and interviewing prospective solution vendors and service providers.
To Gain Their Buy-In: Involve them, and ask for their opinion. Build a plan and allow them to review it and comment. Listen to their concerns. Ask for their support in working with users. Ensure that the vendor you engage will provide support for IT so that your IT team is not overwhelmed with new and expanded tasks and responsibilities.
Executives – Senior executives will be looking at investment costs, return on investment (ROI) and the total cost of ownership (TCO) and at the value you claim this solution will provide. Be prepared before you approach your executive team. Be sure you have involved all the right players and include representatives of these groups to address concerns and answer questions if the executive team wants to probe and challenge.
To Gain Their Buy-In: Be prepared! Keep your presentation at a high level, but be sure you have the details to answer their questions if and when they arise. Provide more detailed reports for them to peruse at their leisure. They probably won’t dive in, but they will be reassured that you have done your homework. Focus your presentation on a) reduction of cost, b) competitive positioning with EXAMPLES of how analytics will help achieve these goals, c) doing less with more and making the company more productive.
Managers – Managers will be concerned about putting more strain on business users and team members and, since the modern approach to business intelligence and analytics involves the business users and their transition to Citizen Data Scientists, you must focus on the managers and what’s in it for them. How does this help them to do their job? They are accountable for results, and they only have so many team members to get the job done. They are also evaluated, based on how their employees see their management style and effectiveness, and they will not want their team to complain.
To Gain Their Buy-In: Focus on their business processes and workflow and how augmented analytics and business user involvement can speed the process, ensure more fact-based decisions and make the managers look good, without putting more strain on the business user. Ensure that your vendor and IT team have a plan to reassure the managers so that they don’t worry about the use of sophisticated systems that will take a lot of training time. How will the roll-out be done? You want a controlled approach so that users are not spending a lot of time getting up to speed and neglecting day-to-day tasks.
Business Users – As usual, the buck stops with the team member. They are the ones who will be asked to change their processes, learn new systems and take on new responsibilities. Look again at the survey results reported above and notice how poor user adoption affected analytics projects. If you can’t get your users to adopt the solution, your project will fail. Your executives, IT team and managers may think this is a great idea, but they will blame you if the team does not respond positively. Involve users in advance to gather and thereby anticipate their concerns when you present your findings and your plan. Do not be defensive. Listen to their issues and incorporate those concerns into your review and selection of a vendor and a solution. With the right self-serve augmented analytics solution and service provider, you can assure them that a) the system will be easy to use and won’t take a lot of time to learn, b) will make their job easier and c) will give them a career advantage.
To Gain Their Buy-In: Listen, digest and address concerns. Understand that there is a culture shift involved in this process and be sure you acknowledge that at all levels of your presentation, including your executive team. Let’s not pretend this new idea will not require change. It will. But if you work with all levels to assure that new responsibilities will be rewarded in employee evaluations and that the team will be supported by managers who are true champions of the process, you will be ahead of the game. Try to meet with users without IT and managers in the room, and then regroup with the appropriate staff (managers, IT etc.) after you have had a chance to evaluate and address user concerns. Users are more likely to be receptive if they aren’t put on the spot. BUT be sure to control the discussion and the environment so it doesn’t turn into a complaint session. When you are ready to do your sales pitch and you have addressed all their concerns, focus on the user and their hot buttons. Tell them how this solution will help them and assure them that the vendor and your implementation team will be there every step of the way. And then follow through!
In this article, we have included just a few of the considerations and factors you will have to address in order to build a plan for your Augmented Analytics project. It is a good idea to engage an IT expert – one with the skills and experience to anticipate your concerns, work with you on industry and business issues and plan for a small, medium or large enterprise installation. An expert team can help you manage the technology review and requirements, and plan for your presentation, etc. Be sure you choose a vendor with sophisticated augmented analytics features and functionality in an easy-to-use environment that will support the transition of your business users to Citizen Data Scientists and ensure that your project will succeed. Contact Us to find out how we can help you plan and achieve your goals. It really IS possible!
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