Self-Serve Cross-Tab BI Tools Reveal Issues and Possibilities!

Self-Serve BI Tools with Cross-Tab Reporting Improve Clarity and Results!

If you are considering a Business Intelligence solution or BI tool, or if you wish to upgrade your business intelligence and reporting tools, look for a solution that has self-serve cross tabulation, or cross-tab reporting. Cross-Tab reporting reveals the relationship between two factors or targets. This analytical tool can be used for side-by-side comparisons and to compare results for one or more data points, variables, or targets.

Did you know that, by some estimates, data-driven businesses are nearly 25% more likely to acquire customers? If you can give your team easy-to-use BI tools with self-serve cross-tab reporting, you can put the power of market and customer knowledge in their hands!

‘Business Intelligence solutions with self-serve cross-tab reporting can provide an intuitive, clear method of data analysis for your business users by revealing relationships in a way that makes the results clear and helps the organization to make the best decisions.’

In this article, we discuss the value of self-serve BI tools with Cross-Tab capabilities and the benefits of this type of focus and insight.

Cross-Tab Reporting Gives Business Users Insight Into Data

Benefits of Self-Serve Cross Tabulation Reporting

Flexible for Business Use Cases

Cross-tab reporting allows for intuitive use by business users with average technical skills, and can be beneficial for all types of business functions and industries. In an educational setting, a university or school might use cross-tab reporting to analyze teacher or course evaluations, looking at the relationship between student satisfaction and the subject, the class time, class location and other factors. Businesses can analyze team and employee satisfaction and attrition by looking at job location, benefits, the results of exit interviews, available training, and support, etc. Cross-tab reporting is frequently used in market research to analyze the various factors that relate to product or service satisfaction, including product features and options, where and how the product is sold, the sales and marketing approach, etc. A retail store owner might use cross-tab data analysis to determine customer satisfaction by looking at demographics, the gender of the person buying the product, the price of the product in a particular region, etc.

Data Clarity

There are many ways to slice and dice data and many ways in which crucial information can hide inside that data. The self-serve cross-tab reporting approach allows business users to examine relationships among data points and factors, with more clarity and accuracy. This type of analysis provides more clarity and reveals results, interdependent relationships and factors that might otherwise be missed. Users can avoid confusion when working with data and analyze large datasets to reveal frequencies and percentages. With this information, the business can understand the ‘what if’ of the various factors and see how results would change if one factor or relationship is changed.

Fact-Based Decision-Making

Self-serve cross-tab reporting simplifies analytics and allows business users to spot trends and patterns and collaborate with other team members to adapt tasks and activities to resolve issues and/or capitalize on opportunities. Using cross tabulation reporting to understand the connection and relationship between two or more factors allows the business to make a decision, with confidence. Rather than guessing the reason for declining results, increased employee attrition or other problems, the enterprise can clearly see what factors (and the relationships among factors) are the cause of a problem and how to change those factors to get better results.

‘If you can give your team easy-to-use BI tools with self-serve cross-tab reporting, you can put the power of market and customer knowledge in their hands!’

Business Intelligence solutions with self-serve cross-tab reporting can provide an intuitive, clear method of data analysis for your business users by revealing relationships in a way that makes the results clear and helps the organization to make the best decisions. By giving your team members these tools, you can leverage domain and industry knowledge and combine data analytics in a day-to-day environment without the need for assistance from data scientists or the IT staff. Self-Serve Cross-Tab reporting produces clear results that are easy to understand and can be used in staff meetings and presentations to support recommendations and help the business become more agile.

Look for seamless Business Intelligence Reporting And Flexible Tools that include self-serve Cross-Tab reporting. Provide business intelligence that your IT team can easily implement and support, and a solution that business users will want to adopt. Choose  flexible, agile business intelligence solutions that can be used at all levels to collaborate, share data, and report and communicate with clarity. Self-Serve BI Tools can provide your business with the foundation to achieve your data democratization and user adoption goals.

Original Post : Cross-Tab Reporting Gives Business Users Insight Into Data!

Business Users Love Simple (Yet Sophisticated) BI Tools!

If You Want Business Users to Embrace BI Tools, You Need to Focus on Simplicity!

If your enterprise has not already adopted business intelligence tools, it is missing a crucial benefit in competitive positioning and accurate, dependable decision-making. If your organization has implemented BI tools, but you are falling short on user adoption success, return on investment (ROI) and total cost of ownership (TCO), it is probably because the business intelligence solution is not meant to support business users.

PC Magazine says that, as business users are asked to leverage BI tools, the enterprise must focus on simplicity to engender user adoption.

‘When your team can access BI tools that support the way they work and provide meaningful views and features to easily integrate with work and business processes, user adoption is easier and more immediate.’

To achieve your enterprise goals, ensure user adoption and get the most out of your investment, you must focus on two things: user-friendly features and function and sophisticated analytics.

BI Tool User Adoption Depends on Simplicity!

In this article, we list some of the considerations for business intelligence solution selection or product upgrade. This list is meant to help you assess your current solution, and/or review the capabilities of any BI tool you are considering.

Simplicity in Technology:

  • 100% browser-based solution
  • Intuitive interface
  • Mobile application that is suitable for iOS and Android
  • Simple, affordable licensing
  • Rapid implementation (roll out in minutes, not months)
  • Simple, multi-layered access and user rights management
  • Simple architecture

Simplicity of Use:

  • Ability to personalize dashboards
  • KPI Reporting
  • Easy-to-use reporting tools
  • Collaborative features
  • Social BI for sharing, ranking and commenting
  • Smart Data Visualization
  • Assisted Predictive Modeling
  • Self-Serve Data Preparation
  • Clickless analytics for easy searching and results

The business intelligence tools you select can and should include out-of-the-box, ready-to-use features that are designed to support your applications, your industry, and/or your business function. When your team can access BI tools that support the way they work and provide meaningful views and features to easily integrate with work and business processes, user adoption is easier and more immediate.

‘To achieve your enterprise goals, ensure user adoption and get the most out of your investment, you must focus on two things: user-friendly features and function and sophisticated analytics.’

Look for Ready-To-Use Tools that users will want to adopt. Provide business intelligence that your IT team can easily implement and support, with features your users will readily leverage. Choose  flexible, agile business intelligence solutions that can be used at all levels to collaborate, share data, and report and communicate with clarity. Self-Serve BI Tools can provide your business with the foundation to achieve your data democratization and user adoption goals.

Original Post : BI Tool User Adoption Depends on Simplicity!

Embedded BI and Augmented Analytics Support ISV Partner Clients!

How Can Embedded BI Help ISV Partners Improve Revenue and Market Visibility?!

Recent research reveals that 67% of companies surveyed say time spent in their applications increased after they embedded analytics. Why do you suppose that is?

Smarten Augmented Analytics Launches PMML Integration Capability!

Smarten has announced the launch of Predictive Model Mark-Up Language (PMML) Integration capability for its Smarten Augmented Analytics suite of products. PMML Integration capability allows data scientists and business users to create PMML Models in other platforms and use those models within the Smarten suite of products without the need for coding.

Smarten CEO, Kartik Patel says, ‘The addition of PMML integration capability enables faster roll-out and allows users to leverage the Smarten workflow for PMML predictive models, adding more flexibility and power to the Smarten suite of augmented analytics tools.’

With Smarten PMML Integration organizations can simplify, streamline, and integrate the analytical process, for swift, clear predictive analytics in a user-friendly environment designed for every business user.

Smarten Augmented Analytics Launches PMML Integration Capability

Smarten PMML Integration enables users to use models created in other familiar platforms like Python, R, Java, KNIME and other platforms, and integrate those models into the Smarten workflow within minutes, without complex coding, scripting, or programming.

‘Smarten PMML Integration enables a seamless process, designed for business users,’ says Patel. ‘Users can import PMML models and enjoy full integration and the full power of the Smarten feature set.’

The ready-to-use Smarten workflow guides the user from validation of the model to roll-out in the production environment. Smarten PMML integration provides simple language interpretation of models and enables predictions using single and multiple test records with user-friendly graphical user interface (GUI) or Web services API.

Simply create the predictive model, using your favorite platform, export the model as a PMML file and import that model to Smarten. Models are interpreted in English and model details are logically organized. Enjoy the Smarten feature set and seamless workflow to perform predictive analytics with support of REST-API for third-party apps for prediction.

Contact the Smarten team to find out how Smarten PMML Integration can support your business needs and your business users with simple features and tools that are suitable for every team member.

About Smarten

The Smarten approach to business intelligence and business analytics focuses on the business user and provides Advanced Data Discovery so users can perform early prototyping and test hypotheses without the skills of a data scientist. Smarten Augmented Analytics tools include Assisted Predictive ModelingSmart Data VisualizationSelf-Serve Data PreparationSentiment Analysis, and Clickless Analytics with natural language processing (NLP) for search analytics. All of these tools are designed for business users with average skills and require no special skills or knowledge of statistical analysis or support from IT or data scientists. Smarten is listed in multiple Gartner Reports including Gartner Data Preparation Report, the Market Guide for Enterprise-Reporting-Based Platforms and the Gartner Magic Quadrant for Business Intelligence and Analytics Platforms Report for the ElegantJ BI Business Intelligence Suite.

Original Post : Smarten Augmented Analytics Launches PMML Integration Capability!

Case Study : Augmented Analytics for a Share Broking & Securities Trading Company in India

Augmented Analytics for a leading Pharmaceuticals Company in Gujarat, India

The client is a leading financial securities firm that offers online digital contacts, transparent trading practices and extends personalized customer service and support. Their services include brokerage, investment advisory, financial services and portfolio management in stock markets, debt markets as well as derivatives markets. The company is a respected corporate member of the National Stock Exchange (NSE) of India.

Case Study : Augmented Analytics for a leading Pharmaceuticals Company in Gujarat, India

Augmented Analytics for a leading Pharmaceuticals Company in Gujarat, India

The client is a leading publicly listed Pharmaceuticals Company with a large shareholder base. The company manufactures all major dosage forms such as Tablets, Capsules, Injectables, Syrups, Ointments, etc.

Case Study : Augmented Analytics for a leading Construction & Infrastructure Development Company in India

Augmented Analytics for a leading Construction & Infrastructure Development Company in India

Founded in 1982 as a construction company, client has successfully positioned itself amongst the top 10 construction & infrastructure management companies in India. Client has to its credit many prestigious projects in the Industrial, Power, Institutional & Infrastructure sectors across India.