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Reporting and Data Visualization Improves Team Understanding!
Statistics reveal that many people learn best when they see a story or information depicted in an image. Graphs, charts with colors, lines and shapes can often tell a story and communicate issues, challenges and opportunities in a business environment.
According to Forbes, ‘Almost eighty-thousand scientific studies attest that visual images promote retention.’
‘Visualization and presentation formats can include personalized dashboards and visualization techniques, alerts for exceptions and trends, and intuitive, mobile BI dashboards.’
Let’s consider a few examples of data presentation to illustrate how images, graphs, charts and visualization techniques can improve data understanding and retention.
Cross Tabulation – Data presentation consists of categorization of data into groups, such as products, geographies, demographics, etc. It can be very useful in understanding sales results, product pricing response, target audience assessment, etc. Cross tab analytics can help your team understand market research, survey responses, seasonality and other factors.
KPI Reports – Key Performance Indicators (AKA KPI) can provide metrics in a dashboard environment that is easy to understand, so users can monitor and manage success factors, and quickly see where there are problems. KPI reporting can be used to identify and capitalize on opportunities and to adjust to challenges in the market and within the walls of the organization.
Custom Print Presentations and Reports – Every organization has a need for custom reports. Needs vary from division to department to user, and these needs can be expensive to accommodate. Custom reports to present data for decision-making, or to monitor results on an ongoing basis are crucial to the organization. But if the enterprise has to ask IT or business analysts or data scientists to satisfy the need, they are losing productivity, time and efficiency. By giving users the ability to design, format and product reports for a particular staff meeting or project, the enterprise can keep the process moving and ensure that the team has what they need to gather, analyze and understand results in a meaningful way. Custom formats might include customer statements, management reports, compliance reports, project templates, etc. Users can present data in a clean, colorful, attractive way to satisfy customers, partners, suppliers, executives and team members.
‘According to Forbes, ‘Almost eighty-thousand scientific studies attest that visual images promote retention.’
These are just a few examples of reporting formats and types, and how they might help your enterprise. Other types of visualization and presentation formats can include personalized dashboards and visualization techniques, alerts for exceptions and trends, and intuitive, mobile BI dashboards.
Team members, managers and executives typically think of reporting and presentation as boring, detailed and unintelligible. They rarely see the value in using data to make decisions when, in fact, this approach is the wisest and produces the best results. But it is understandable that the staff, customers, partners and suppliers would cringe when a report is placed in front of them, emailed to them or presented on a screen.
What if you could create, format, present and share data in a way that quickly communicated results, delivered a message, identified an issue or illustrate dan opportunity? Change the way your enterprise uses and interacts with data, with clean, clear, concise, elegant and colorful presentation.
Explore the benefits of Smarten Reports, and Pixel Perfect Print Reports and the use of this this seamless PDF Pixel Perfect Reports Solution, and the Smarten suite of Augmented Analytics can support your business users with self-serve tools that are intuitive and will encourage user adoption and fact-based decision-making.
Original Post : How Can Data Visualization Help Me Achieve Business Results?
What Are the Advantages of Low-Code, No-Code Platform in Augmented Analytics Solutions?
According to some estimates, the rise of low-code, no-code and AI in analytics has increased access to augmented analytics to end-users by 36% to 56%. In fact, Gartner predicts that 75% of new global software solutions will incorporate a low-code approach.
In the analytics software market, the primary driver of this growth is the advent of solutions that can be quickly modified and upgraded to address new requirements and user needs. The creation of no-code and low-code apps allows for simple foundations and construction to analyze data without customization or programming or data science skills supports both developers, data scientists and power users of analytics by providing tools to simply and easily create complex components.
‘When considering an augmented analytics solution, prospective users should carefully review the foundation and technology of the analytical software. The incorporation of new technologies and capabilities will drive current and future user adoption and the successful implementation of analytics within the business user community.’
The organization can leverage and change data workflows, reports, dashboards and predictive models without extensive coding or time investment. While Low-Code development enables organizations to build apps with minimal coding, No-Code utilizes a suite of tools, scripts and components to allow swift construction of apps with very limited coding or user interface (UI) based configurations. Both of these approaches enable a development environment that is agile, and can quickly respond to the changing needs of users, customers and the organization.
With this approach, users enjoy access to data, models, charts, gauges, tables, and grids that satisfy their current needs, and these can be easily modified as the organization grows and changes, and the user requirements evolve.
There are numerous benefits and advantages to incorporating low-code, no-code into an analytical environment, and these benefits provide support for developers, data scientists and for power business users.
- Supports Complex Data Extraction, Transformation and Loading (ETL) and Data Preparation Workflows Throughout the Data Pipeline
- Enables Complex Data Transformation and Data Cleansing Functions
- Offers Rapid Predictive Modeling Hypothesis and Prototyping
- Allows Quick, Easy Construction of Custom Expressions
- Enables User Adoption of Self-Serve Analytics and the Citizen Data Scientist Culture
- Requires No Professional Programming or Scripting Experience – Power Users Can Perform Complex Tasks Without Assistance
- Supports Data Democratization and Data Literacy
- Allows for Rapid Development of Various Analytics Components e.g., Datasets, Dashboards, Rports and Models
- Ensures Agility and Speed of Upgrades
- Provides a Cost-Effective Solution with Personalization for Organizations
- Offers Flexible Integration and Data Management
- Reduces Cost
- Improves Collaboration and Productivity
- Improves Return on investment (ROI) and Total Cost of Ownership (TCO).
‘Gartner predicts that 75% of new global software solutions will incorporate a low-code approach.’
When considering an augmented analytics solution, prospective users should carefully review the foundation and technology of the analytical software. The incorporation of new technologies and capabilities will drive current and future user adoption and the successful implementation of analytics within the business user community. Technologies and techniques like low-code, no-code, artificial intelligence (AI), and embedded business intelligence (BI) to provide access to analytics from within enterprise applications, will support data democratization, data literacy and fact-based decision-making within the enterprise.
Smarten Augmented Analytics with low-code, no-code technology will support your team with tools that are intuitive and easy to use and will encourage user adoption. Leverage the essential components of the Smarten Technology foundation, and improve decision-making and outcomes. Explore the potential and capabilities of the Smarten Cloud software-as-a-service (SaaS) product with its low-code, no-code foundation and seamless functionality.
Original Post : The Low-Code, No-Code Approach to Augmented Analytics!
A Citizen Data Scientist Initiative Can Optimize Data Scientists and Encourage a Data-Driven Culture!
According to some estimates, the average salary of a Data Scientist in the United States is over $150,000 per year. If your business wishes to accommodate a ‘data-first’ strategy to improve metrics and measurable success and avoid guesswork and strategies that are based on opinion rather than fact, it can either employ a team of expensive professionals, or it can take a different approach.
‘Citizen Data Scientists can use their knowledge of a business sector, industry, function or market to drive questions and develop reports and presentations to illustrate issues, identify problems and find opportunities for growth and competitive positioning, and share this data (and the search and analytical techniques) with other users.’
Citizen Data Scientists are business users who have a place on your team and are hired because of their professional and career experience in a particular industry, business function or discipline. When they are given access to data analytics, they can merge their knowledge of an industry, e.g., research, healthcare, law, finance, sales, supply chain, production, construction etc., with data integrated from databases, best-of-breed software programs, ERP, SCM, HRM and other systems and use sophisticated analytical tools in an easy-to-use, intuitive environment to gather and analyze data and produce insightful, concise results that are meaningful to their role.
Depending on the size, market and industry of your business, you may choose to augment your staff with one or more data scientists to refine results produced by Citizen Data Scientists on a day-to-day basis. So, if a power user or business users discovers a challenge or an opportunity and your management team wishes to further explore the issue to understand its strategic or operational value, a Data Scientist can take the predictive model or other analytical report produced by a Citizen Data Scientist and refine the results for executive review.
Whether you choose to employ the services of a Data Scientist, provide business analysts or IT professionals to support your business users, you can create a comprehensive foundation for analytics across your organization.
By democratizing data analytics you can achieve many benefits, including:
- Improved Data Literacy Across the Enterprise
- Improved Productivity of Data Scientists, IT and Business Analysts (who can spend time on strategic initiatives rather than producing daily reports)
- Optimized Return on Investment (ROI) and Total Cost of Ownership (TCO) for all software and systems
- Fact-Based Decisions and Metrics-Driven Strategies, Goals and Objectives
- Team Member Career Advancement
- Optimization of Resources and Improved Team Productivity
A comprehensive self-serve augmented analytics solution will include Modern Business Intelligence (BI) and Reporting with Key Performance Indicators (KPIs), Self-Serve Data Preparation, Assisted Predictive Modeling, and Smart Data Visualization with auto-suggestions to drive the analytical techniques and illustration of data based on data type, volume, etc., and other tools like Embedded BI, Mobile BI, Key Influencer Analytics, Sentiment Analysis, and Anomaly Alerts and Monitoring.
With these tools, the Citizen Data Scientist can leverage Natural Language Processing (NLP) and search analytics with machine learning to ask questions using simple human queries and receive insightful answers. They can use their knowledge of a business sector, industry, function or market to drive questions and develop reports and presentations to illustrate issues, identify problems and find opportunities for growth and competitive positioning, and share this data (and the search and analytical techniques) with other users.
Citizen Data Scientists can predict customer responses to new product features, and to new marketing campaigns, analyze the likelihood of fraud or risk, identify supply chain issues, etc. These tools can also help the organization to foster collaboration and data sharing and encourage business users to innovate, create and explore opportunities using data-driven, factual information.
‘When Citizen Data Scientists are given access to data analytics, they can merge their knowledge of an industry, e.g., research, healthcare, law, finance, sales, supply chain, production, construction etc., with data integrated from databases, best-of-breed software programs, ERP, SCM, HRM and other systems and use sophisticated analytical tools in an easy-to-use, intuitive environment to gather and analyze data and produce insightful, concise results that are meaningful to their role.’
These are just a few of the factors you must consider when implementing a Citizen Data Scientist approach. Business users who are interested in becoming a Citizen Data Scientist must be willing to embrace new technology and tools and working at the leading edge of a new approach to collaboration and decision-making. initiative. Consider engaging an expert for your Citizen Data Scientist. IT consultants with experience and skill in this area can provide crucial support to help you succeed with your Citizen Data Scientist initiative and can provide simple Training Programs to bring your team on board and help them see the value to themselves and to the organization.
Original Post : Leverage Citizen Data Scientists to Augmented Data Scientist Teams!
The Client is an India-based construction and infrastructure development company, committed to delivering quality infrastructure for private, public, and government projects. With over fifty (50) years of accumulated knowledge and experience, the organization applies its extensive resources to ensure superior infrastructure solutions.
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Assisted Predictive Modeling Enables Business Users to Predict Results with Easy-to-Use Tools!
Gartner predicted that, ‘75% of organizations will have deployed multiple data hubs to drive mission-critical data and analytics sharing and governance.’
With all of this business data, how can your organization a) help your team gather and use data to make fact-based decisions, and b) use that data to predict which products and services your customers will need in the future, how your customer buying behavior is shifting, how your competition will respond to the market, when and how to sell your products, which marketing campaigns will work in the future, and how and when to recruit new resources and open new locations.
‘Giving your team access to sophisticated, complex analytical techniques in an intuitive environment, allows them to leverage predictive analytics without a data scientist or analytical background.’
A misstep in any of these areas can create risk, damage your business reputation, or put you years behind your competition. That’s why your business needs predictive analytics. And, not just any predictive analytics! If you want to democratize data among your team members and provide easy-to-use tools to encourage user adoption and enable data-driven decisions, you must choose wisely.
Assisted predictive modeling can take the guesswork out of analytics, by helping users to choose the right techniques to analyze the type and volume of data they use to analyze. These tools allow the organization to apply predictive analytics to any use case using forecasting, regression, clustering and other methods to analyze an infinite number of use cases including customer churn, and planning for and target customers for acquisition, identify cross-sales opportunities, optimize pricing and promotional targets and analyze and predict customer preferences and buying behaviors.
Prescriptive analytics for regression models combines predictive modeling and optimization techniques to produce actionable recommendations for decision-making. While descriptive and predictive analytics use past events to predict future outcomes, prescriptive analytics goes beyond this process to recommend optimal actions that will help the business to achieve specific goals. By merging prediction with prescription, the enterprise can proactively identify challenges and opportunities, and drive more effective and strategic outcomes.
These are just some of the tools your business should consider to build a solid foundation for predicting outcomes using historical and forward-looking data analytical techniques.
Giving your team access to sophisticated, complex analytical techniques in an intuitive environment, allows them to leverage predictive analytics without a data scientist or analytical background. Your users can access:
- Time Series Forecasting
- Regression Techniques
- Classification
- Association
- Correlation
- Clustering
- Hypothesis Testing
- Descriptive Statistics
‘Assisted predictive modeling can take the guesswork out of analytics, by helping users to choose the right techniques to analyze the type and volume of data they use to analyze.’
With the right predictive analytics solution, your business can also support data scientists, IT and business analysts with tools that allow for R script integration, so these users can perform complex statistical and predictive analysis and reporting to support strategic organizational needs.
Smarten Assisted Predictive Modeling will support your team with tools that are intuitive and easy to use and will encourage user adoption. Leverage the essential components of Augmented Analytics and improve decision-making and outcomes.
Original Post : Leverage Predictive Analytics for Every Business User!
The Client is a state government with a population of approximately 30 million citizens, and an annual budget of $5 billion USD. This government agency focuses on implementing IT and e-governance initiatives to enhance citizen services and governance efficiency. By leveraging advanced technology, the agency aims to improve the quality of life for citizens and to streamline administrative processes across and throughout departments.
What Do I Need to Know Before I Choose a Mobile Business Intelligence (BI) Solution for My Business?
What makes a great Mobile Business Intelligence (BI) solution? There are many factors to consider and, if you do not choose wisely, you risk a) spending a lot of money and getting very little in return, b) working with incorrect, old or incomplete data, c) having to upgrade and spend even more money, d) disappointing your team and falling short of objectives, e) missing your Citizen Data Scientist initiative goals.
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