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