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).
Tag: Data Literacy
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.
Smart Data Visualization and Personalized Dashboards Improve Data Insight and Team Collaboration!
Augmented Analytics was designed to remove the barriers erected by the traditional business intelligence and analytics solutions. In order to achieve data democratization and improve data literacy among team members within an enterprise, the organization must provide simple, easy-to-understand solutions that display analytical results in a way that is meaningful and intuitive.
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!
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.
Original Post: Citizen Data Scientists Need These 3 Things to Succeed!
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Smarten is pleased to announce that its Smarten Augmented Analytics solution is included as a Representative Vendor in the Market Guide for Augmented Analytics Published October 2, 2023 (ID G00780764).
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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.
Enterprise Agility and Adaptability Are Crucial. The Right BI Tools Can Help!
Gartner research states that, ‘90% of corporate strategies will explicitly mention information as a critical enterprise asset and analytics as an essential competency.’
Whether yours is a small or a large business, your success today depends upon your agility and adaptability and those characteristics also apply to your data and your information.
If you are to build a flexible business environment, you must have tools and solutions that allow you to monitor and manage data and information and use that data to make fact-based decisions.
‘Comprehensive BI Tools should provide data analytics access for all business users and, above all, provide flexible, agile solutions that can be used at all levels to collaborate, share data and report and communicate with clarity.’
When considering a business intelligence (BI) solution, choosing a self-serve tool serves two purposes:
Support for the Organization and Users
A business can provide software and tools for users, but if those tools are not user-friendly, or if team members do not perceive their value, they will not adopt the solution into their business processes. In order to ensure that the organization can expect a good return on investment (ROI) and a low total cost of ownership (TCO), the enterprise must select a BI tool that is useful to the team and can easily be applied to satisfy the needs of their role and their responsibilities. The tools must also provide self-serve tools that offer comprehensive predictive analytics, key performance indicators (KPIs), flexible reporting, self-serve data preparation, deep dive analytics, mobile BI and social BI. This foundation will allow business users to improve data literacy and perform analytics with confidence, thereby improving fact-based decision-making.
Flexibility and Agility
When the organization selects business intelligence tools that are flexible, users can leverage personalized dashboards and customize their use to serve the needs of their role, their team and their business unit. The ability to adapt quickly by finding the root cause of a problem, spotting a trend and addressing that trend or identifying an opportunity to improve competitive advantage can provide an edge in the market and allow the organization to move quickly. Users can collaborate and share data to make decisions and recommendations and suggestions are clearly supported by data, so there is no hesitation or delay.
‘If you are to build a flexible business environment, you must have tools and solutions that allow you to monitor and manage data and information and use that data to make fact-based decisions.’
Comprehensive BI Tools should provide data analytics access for all business users and, above all, provide flexible, agile solutions that can be used at all levels to collaborate, share data and report and communicate with clarity. Simple, Self-Serve BI Tools can provide your business with the foundation to achieve your data democratization and user adoption goals. Let us help you achieve your vision and improve productivity and insight across the organization.
Original Post : Choose Self-Serve BI Tools to Support Business Success!
