Tag: Augmented Analytics Company Ahmedabad

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!

Simplify and Improve Analytics with Self-Serve Data Prep!

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January 30, 2024

Self-Serve Data Preparation Transforms Business Users to Citizen Data Scientists!

Data Scientists spend a lot of time gathering and preparing data for analysis, and that is time they could spend more productively performing tasks that add value and strategic direction. Business users cannot even hope to prepare data for analytics – at least not without the right tools.

Gartner predicts that, ‘data preparation will be utilized in more than 70% of new data integration projects for analytics and data science.’ So, why is there so much attention paid to the task of data preparation? It’s simple. Because, without the right preparation, analytics can produce incomplete, incorrect results, thereby sending the business off in the wrong direction and resulting in a loss of confidence in analytics for decision-making.

‘Self-Serve Data Preparation can benefit your business users and help to transform them into Citizen Data Scientists.’

When an enterprise chooses the right self-serve data preparation tools, it can confidently use these tools to prepare for and execute analytics that will result in concise, clear results that benefit the organization, its users and its customers and stakeholders.

Self-Service Data Prep empowers every business user and allows them to prepare data for their analytics using tools that enable data extraction transformation and loading – ETL for business users! In other words, business users can quickly move data into the analytics system without waiting for IT.

Self-Serve Data Prep Provides Numerous Benefits

The right self-serve data prep solution can provide easy-to-use yet sophisticated data prep tools that are suitable for your business users, and enable data preparation techniques like:

  • Connect and Mash Up
  • Auto Suggesting Relationships
  • JOINS and Types
  • Sampling and Outliers
  • Exploration, Cleaning, Shaping
  • Reducing and Combining
  • Data Insights (Data Quality Index)
  • Data Lineage and Collaboration
  • Data Searching, Profiling and Cataloguing

Users can:

  • Test hypotheses, visualize data and create and share reports with others, thereby encouraging collaboration, data sharing and data literacy
  • Prepare and work with data without advanced data science or analytical skills
  • Grow data skills and confidence and transform into Citizen Data Scientists
  • Significantly improve data quality with machine learning and statistical tools that are easy-to-use
  • Prepare data for visualization and analysis quickly and easily
  • Remove irrelevant, out-of-date and inappropriate data before analysis
  • Create and re-use datasets with contextual metadata
  • Move data into analytics system without waiting for assistance from the IT team

‘Self-Service Data Prep empowers every business user and allows them to prepare data for their analytics using tools that enable data extraction transformation and loading.’

Find out how Self-Serve Data Preparation 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: Simplify and Improve Analytics with Self-Serve Data Prep!

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?”

Case Study : Smarten Augmented Analytics Case Study- Pharmaceutical, Clinical Research and Innovation Company

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September 29, 2023

The Client is a global business governed by a foundation whose mission is to have a meaningful social impact, both for patients and for a sustainable world. With its unique governance model, the Client business can fully serve its vocation with a long-term vision and fulfil its commitment to therapeutic progress and to serving patient needs. The company has grown exponentially, first across France and then throughout the world, driven by the transformation of the business.

Continue reading “Case Study : Smarten Augmented Analytics Case Study- Pharmaceutical, Clinical Research and Innovation Company”

Use a BI Tool with Cross-Tab Deep Dive Features!

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January 20, 2023

Why It’s Important to Include Cross-Tab Deep Dive in Self-Serve BI Tools!

When a business decides to implement a self-serve business intelligence (BI solution, it must ensure that the tools really are ‘self-serve’ and that they provide the flexibility and agility to give power users the ability to create and analyze, and business users with average technology skills the ability to quickly and easily understand the augmented analytics tools they now have access to, and to use those tools to the benefits of the team and the organization.

Continue reading “Use a BI Tool with Cross-Tab Deep Dive Features!”

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!

Predictive Analytics Business Use Cases Ensure Results!

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September 27, 2022

Apply Predictive Analytics to Specific Business Use Cases for Real Results!

Gartner has predicted that, ‘Overall analytics adoption will increase from 35% to 50%, driven by vertical and domain-specific augmented analytics solutions.’ Your business, like every other business in the world, has its own industry, domain and vertical concerns, and these concerns drive your competitive strategy, your products and your services.

Predictive analytics uses sophisticated analytical methodologies to predict future outcomes based on historical data. Using these techniques, the organization can predict future events, customer buying behaviors, and business outcomes. These techniques can help the business drive results, improve revenue, understand customer and client buying behavior, solve problems, plan for new locations and products, create accurate pricing strategies and plan for new resources and training, as well as for appropriate maintenance, supply chain services, etc.

‘Take the guesswork out of the planning process and analyze factors that influence business success. Plan and forecast accurately.’

Predictive Analytics utilizes various techniques including association, correlation, clustering, regression, classification, forecasting and other statistical techniques. These techniques can be targeted to specific business use cases to solve specific, unique business issues and to help the business plan, forecast and compete.

In order to understand how businesses might use assisted predictive modeling and predictive analytics, let’s look at some business use cases and how analytical techniques can help the enterprise derive concise, clear information to support decisions and strategies.

Minimum Viable Products (MVP) Produces Better Business Start-Up Results

Customer Churn

The cost of acquiring and interacting with customers can be expensive and each time a business loses a customer, it must spend money to replace the customer.

Fraud Mitigation

Businesses must mitigate fraud and control business costs and must develop and sustain fraud detection processes to monitor operations.

Quality Control

Businesses must control quality or risk losing customers and market share and exposing the enterprise to legal risk and liability.

Demand Planning

Take the guesswork out of the planning process and analyze factors that influence business success. Plan and forecast accurately.

Product/Service Cross-Selling

Leverage customer satisfaction to cross-sell and upsell products and services and increase revenue and brand loyalty.

Maintenance Management

Focus on equipment maintenance to ensure that downtime is limited and equipment is up and running, anticipate resources, hours on the job and training needs.

Customer Targeting

Identify the reasons customers buy a product or service and use fact-based data to create products, marketing campaigns, ads and customer outreach. Target specific demographics and customers.

Human Resource Attrition

The enterprise must retain team members and to do so, it must understand what makes a team member stay or go, what makes them invest in the future of he business and what issues create issues and dissatisfaction.

Loan Approval

The enterprise must avoid bad loans, so as to enhance profitability and productivity and it must have a dependable process for identifying and attracting the right clients and for reviewing, approving and managing loans.

Marketing Optimization

Create attainable targets and goals with an understanding of what improves and affects sales and how customers choose a product or service, how to market and advertising to achieve objectives.

Predictive Analytics Using External Data

Integrate external data and analyze data to assess the affect on sales, marketing, finances, resources, productivity, etc.

Online Target Marketing

Optimize marketing funds and resources, understand what works and what does not work, and how, when and where to message and the ideal demographic and profile of the target customer.

Student Academic Performance

Predict academic performance of students to effectively manage student interaction and training and improve environment to assure student success.

Crime Type Prediction

Predict the type of crime that is likely to occur to plan for appropriate law enforcement resources, placement and strategies and ensure public safety and appropriate use of funds.

‘Predictive Analytical techniques can be targeted to specific business use cases to solve specific, unique business issues and to help the business plan, forecast and compete.’

Find out how Assisted Predictive Modeling and Augmented Analytics can help your business plan for success, and explore the potential of comprehensive Predictive Analytics here.

Original Post : Predictive Analytics Business Use Cases Ensure Results!

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!

Get the Right Predictive Analytics Tools for Users!

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August 5, 2022

Can Predictive Analytics Provide Accurate Results for My Business Without Burdening My Users?

If your business is struggling to forecast and predict outcomes and results, your management team is probably considering predictive analytics. The technology research firm, Gartner, states that, ‘50% of data scientist activities will be automated by artificial intelligence, easing the acute talent shortage.’

For the average team member, the concept of predictive analytics may seem daunting and, if you are a business user whose management team has asked you to embrace and participate in analytics, the addition of predictive analytics to your day-to-day business processes may seem irrelevant or it may seem to mean you will be expected to work harder or produce more output. But don’t be too quick to assume the worst.

‘By providing this type of expanded functionality to the team, the business can enable both data scientists and business users with predictive analytics that will benefit the organization.’

Let’s take a look at Predictive Analytics, the benefits of Assisted Predictive Modeling and its importance in the organization and how intuitive augmented analytics can help business users achieve their goals without requiring advanced training or additional workload.

Predictive Analytics Can Make Business Users Happy!

What is Predictive Analytics?

Predictive analytics is comprised of sophisticated analytical methodologies that allow businesses to predict future outcomes based on historical data. Using these techniques, the organization can predict future events, customer buying behaviors, and business outcomes. Predictive Analytics utilizes various techniques including association, correlation, clustering, regression, classification, forecasting and other statistical techniques.

Understanding Assisted Predictive Modeling

When a business provides augmented analytics tools for business users, it allows the team to perform predictive analytics on a daily basis without the assistance or skills of a Data Scientist or an IT professional. Assisted Predictive Modeling provides auto-suggestions and recommendations to guide business users with recommended techniques, selecting the most appropriate techniques for the type and volume of data the user wishes to analyze. If the business chooses an augmented analytics tool with intuitive predictive modeling features, it allows users to work quickly and receive clear, concise results for decision-making so user adoption of the tools is more likely and forecasting and predictions are accurate and timely. All popular predictive modeling techniques are incorporated into the solution, so users have access to the most sophisticated predictive analytics and tools and can use these tools to model and review business use cases and issues.

The Benefits and Importance of Assisted Predictive Modeling

These tools allow the organization to apply predictive analytics to real use cases to analyze customer churn, to target customers, to identify cross-selling and product bundling, to find and set appropriate price points, to forecast where and when to open new locations, when the business will need new suppliers, when equipment will require maintenance, etc. A comprehensive augmented analytics solution also includes the benefit of integration with R Script, so that data scientists can capitalize on expertise and leverage enterprise investments in R open-source platforms, to perform statistical and predictive algorithms, and complex analysis to provide the depth of detail and advanced analytics and reporting the organization needs for strategic decision-making. By providing this type of expanded functionality to the team, the business can enable both data scientists and business users with predictive analytics that will benefit the organization, encourage collaboration and data sharing, and improve data literacy – all without increasing workload or frustrating users and team members.

‘Intuitive assisted predictive modeling and augmented analytics can help business users achieve their goals without requiring advanced training or additional workload.’

Find out more about Assisted Predictive Modeling and Augmented Analytics and explore the potential of comprehensive Predictive Analytics here. Find out how it can improve user adoption of analytics and increase accuracy of forecasting and results.

Original Post : Get the Right Predictive Analytics Tools for Users!

Augmented Analytics Use Cases for Citizen Data Scientists!

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August 1, 2022

Enable Citizen Data Scientist User Adoption of Augmented Analytics with Business Use Cases!

Gartner research states that, ‘90% of corporate strategies will explicitly mention information as a critical enterprise asset and analytics as an essential competency.’ This prediction is supported by initiatives in businesses around the world, as the average enterprise recognizes the value of fact-based decisions and improved business agility.

For a business to succeed in transforming business users to Citizen Data Scientists, it must have a firm grasp on how to use – and encourage team members to use – augmented analytics. Simply providing the advanced analytics solution and integrated data across the enterprise does not ensure user adoption. But, if a user can understand how these solutions will make their jobs easier, and how augmented analytics can help a team member improve their contribution, speed the business process and increase their career potential, user adoption is more likely.

‘Appropriate Citizen Data Scientist training and organizational planning will provide a solid foundation and build business user confidence by providing an introduction, fundamental information and the tools these users will need to succeed.’

In this article, we explore a few examples of business use cases to illustrate how a business user can examine real world business issues within the augmented analytics environment to create data stories and reveal clear, concise results to support recommendations and actionable direction.

Citizen Data Scientists Employ Business Use Cases to Succeed

Customer Churn

By understanding why customers abandon your business, you can address the root causes and issues that create customer churn and prioritize these issues to address the most important factors first. You can alter marketing messages and campaigns to improve results and even create new products or services that will improve customer satisfaction and retention.

Among the many considerations you might analyze for customer churn, your business use case might include services that each customer uses like phones, the number of phones lines, internet services, online security, online backup, device protection, tech support, and streaming TV and movies or you might look at customer account information such as how long they have been a customer, the contract length and detail, payment method, paperless billing, monthly charges, and total charge. Customer churn analysis might also include demographic information about customers like gender, age range, and if they have partners and/or dependents

When considering customer churn analysis, one might use the binary logistic regression technique.

Product and Service Cross-Selling

The use case for product and service cross-selling and up-selling is useful to understand what your customers like, and where you can cross-sell, bundle or up-sell other products by leveraging what you know about your customer’s buying behavior. Every business needs to know what makes a customer buy or try another product and what features, design or product or service combinations might help the business sell more units. For example, a retail store manager may want to analyze the optimal and strategic placement of various products in order to increase cross sales.

By looking at transactions, the date of a purchase and what the customer purchased, the business can develop a comprehensive understanding of behavior and brand loyalty. The enterprise will benefit by increasing revenue, targeting new products and services, creating marketing messages to target a particular customer demographic and improving brand loyalty and the product and service mix. One could consider the date of purchase and the products purchased to find item combinations and the frequency of purchase.

To perform analysis on this type of use case, the business might use Frequent Pattern Mining.

Human Resource Attrition

This use case focuses on human resource attrition. Like customer retention, human resource retention is important because stable retention eliminates the cost of advertising, interviewing, hiring and training a new employee. Human resource attrition analysis allows the business to see which employees are likely to leave and which will remain loyal, based on tenure, training, job responsibilities, and other factors.

The analytical data set will include pay, performance and reward information, past work experience, team member demographic information like gender, age, education, marital status and employment tenure, as well as job satisfaction rankings for things like satisfaction with pay, and surveys and more. The business might also include performance-reward contingencies.

By reducing employee turnover, the business can improve hiring and screening processes, optimize human resources and compensation, improve training programs and increase employee loyalty and satisfaction.

For this business use case, the business might use the Binary Logistic Regression technique.

For any or all of these Business Use Case examples or any of the many other use cases a team member might want to examine, the augmented analytics solution will provide a sophisticated underpinning of machine learning, natural language processing (NLP) search capability and an intuitive interface to enable and speed the analytics process with tools that are designed for the average business user and require no data science or IT experience or knowledge.

‘For a business to succeed in transforming business users to Citizen Data Scientists, it must have a firm grasp on how to use – and encourage team members to use – augmented analytics.’

Transforming business users into Citizen Data Scientists, provides advantages to the organization, to the business users and to data scientists. Appropriate Citizen Data Scientist Training and organizational planning will 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 : Augmented Analytics Use Cases for Citizen Data Scientists!