Author: Smarten

Data Insights Assure Quality Data and Confident Decisions!

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November 26, 2024

Why is Data Insight So Important?

Every business (large or small) creates and depends upon data. One hundred years ago, businesses looked to leaders and experts to strategize and to create operational goals. Decisions were based on opinion, guesswork and a complicated mixture of notes and records reflecting historical results that might or might not be relevant to the future.

Today, organizations look to data and to technology to help them understand historical results, and predict the future needs of the enterprise to manage everything from suppliers and supplies to new locations, new products and services, hiring, training and investments. But too much data can also create issues. If the data is not easily gathered, managed and analyzed, it can overwhelm and complicate decision-makers.

‘Data insight techniques provide a comprehensive set of tools, data analysis and quality assurance features to allow users to identify errors, enhance data quality, and boost productivity.’

By some estimates, bad data costs global organizations more than five trillion USD annually.

Use Data Insight Techniques and Data Quality Management and Analytics to Achieve Better Results

Data insight takes data to the next level by providing comprehensive data analysis and quality assurance features that empower business analysts and users to quickly and easily identify errors, enhance data quality, and boost productivity. The business can harness the power of statistics and machine learning to uncover those crucial nuggets of information that drive effective decision, and to improve the overall quality of data.

By incorporating machine learning, natural language processing and automation within advanced analytics solutions, the enterprise can improve results and support its team with augmented analytics that are designed as self-serve solutions for business users, so the team can gather and analyze information with ensured, sustained data quality and results that are clear and concise. When an analytics solution is built upon this foundation, with advanced tools and techniques to support users, the enterprise can ensure user adoption and positive outcomes. Users do not have to learn complex systems or look to data scientists or business analysts for answers.

Tools that support data insight include numerous data quality management techniques. These tools allow users to see and work with datasets in a way that is targeted and provides clear, actionable information for decisions and strategies.

Overview – Reveals the data quality index in percentage representing the quality level of data. It shows the quality of the dataset and number of columns with listing down the missing values, duplicates, and measure and dimension columns.

Observations – Highlights all detected inconsistencies and anomalies within your dataset, along with the corresponding column names. By clicking on a column name, you can access detailed information about the observation for that particular column and view recommendations for fixing the issue.

Column Analysis – Shows the details related to all the columns in the dataset. It categorizes the columns by their types and shows Sample values, Missing Values, Most frequent values, least frequent values, Unique values and Quality index of that column.

Column Associations – Shows the pairs associations between all columns which helps you to understand the relationship with each other. The degree of association can be determined by the index value, and higher the index indicating a stronger relationship between columns.

Feature Importance – Automatically identifies and displays the target variable along with its key predictors from your dataset. It also shows the influence of each predictor on the target. This helps you select the predictors that have the greatest impact, making it easier to create an effective predictive model.

Missing Value Analysis – Shows the analysis of the missing values across all the columns of the dataset at a glance. The graph visually represents both non-missing (non-null) values and missing (null) values, allowing you to quickly identify which columns have incomplete data.

Column Metadata – Provides information on the dataset’s recency, such as the last update and publication dates. It will also talk about the details like Datatype, Column Type and respective Sample Value of the columns in dataset.

Settings – Customize the data insights computing process for datasets to lower the load and processing time.

Data insight and Data Quality Management tools and techniques provide a comprehensive set of tools, data analysis and quality assurance features to allow users to identify errors, enhance data quality, and boost productivity. Users can uncover hidden insights and improve the overall quality of data with actionable recommendations to take prompt action.

‘By some estimates, bad data costs global organizations more than five trillion USD annually.’

To find out more about Natural Language Processing (NLP), Machine Learning And NLP Search Analytics, and comprehensive data quality management and Data Insight Tools, Contact Us. Discover the power of Augmented Analytics, machine learning, and Natural Language Processing (NLP). Read our free article, ‘Why Is Natural Language Processing Important To Enterprise Analytics?’.

Original Post: Data Insights Assure Quality Data and Confident Decisions!

Low-Code/No-Code Analytics Design Engenders Solution Agility!

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November 18, 2024

Look for Analytics with Low-Code/No-Code Technology!

The advent of low-code, no-code app and software development has enabled rapid, innovative changes to all types of development projects and that new environment is evident in Modern Business Intelligence (BI) and Augmented Analytics products and solutions.

Continue reading “Low-Code/No-Code Analytics Design Engenders Solution Agility!”

Case Study : Augmented Analytics Solution for Large Indian Construction and Infrastructure Company!

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November 13, 2024

Augmented Analytics Solution for Large Indian Construction and Infrastructure Company

The Client is a prominent Indian construction and infrastructure company providing services in numerous sectors, including highway, rail, mining, energy, irrigation, and water supply. Known for their expertise in managing large-scale and complex projects, the Client has played a significant role in enhancing the India infrastructure and has achieved robust growth and financial stability. The Client is currently managing sixty two (62) projects and employs more than 5000 employees in numerous market sectors across India.

Continue reading “Case Study : Augmented Analytics Solution for Large Indian Construction and Infrastructure Company!”

Why Should Business Users WANT to be a Citizen Data Scientist?

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November 7, 2024

Making the Case for Citizen Data Scientists!

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.

Continue reading “Why Should Business Users WANT to be a Citizen Data Scientist?”

Smarten Support Portal Updates – October – 2024!

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November 4, 2024

We invite you to explore our latest knowledgebase articles and to join the Smarten user community on Smarten Support Portal.

If you have not registered yet, Click Here to obtain your login credentials.

Knowledgebase Articles

  1. Access Rights, Roles and Permissions : AD Integration in Smarten
  2. Data Sources : Database Data Sources : Improving performance for fetching data from the database
  3. GeoMap : Importing areas and their Lat / Long

Predictive Use cases

  1. Assisted predictive modelling : Regression : Medical Cost Prediction Using Smarten Assisted Predictive Modelling
  2. Assisted predictive modelling : Classification : Customer Churn model using Smarten Assisted Predictive Modelling

Business Use Cases

  1. Help & Manuals : Minimizing Number of Steps using Custom SQL in SSDP
  2. Help & Manuals : How to derive the recently purchased city of each customer from daily customer transactions from various cities

Manuals and Technical Guides

  1. Smarten-Concept-Manual-SSDP
  2. Smarten-Working-with-Key-Influencers
  3. Smarten-Securing-Application-Server

If you don’t find what you need in the Support Portal, we hope you will contact us with your questions, comments or suggestions. We are here to help and to support your business goals and success!

URL: Smarten Customer and Partner Community
Email: support@Smarten.com

Original Post: Smarten Support Portal Updates – October – 2024!

Give Business Users NLP Search Analytics and Get Results!

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October 24, 2024

NLP Search Analytics Ensures User Adoption

These days, most people understand the term Natural Language Processing (NLP). It has been around a while, and represents perhaps the most significant information tool in the past century.

Machine Learning and Natural Language Processing (NLP) have unlocked a vast library of knowledge, making it accessible to the average person, requiring no significant technical skills, and leveling the playing field for millions of people, seeking to learn and understand the world.

‘NLP search technology significantly simplifies the user experience and encourages team members to learn and incorporate augmented analytics into their daily activities.’

Just a few years ago, Gartner predicted that, ‘50% of analytical queries will be generated via search, NLP or voice, or will be automatically generated.’ Today, this prediction is a reality.

When an enterprise wishes to implement augmented analytics and business intelligence, and make these tools available to its business user community, it must select a solution that uses natural language processing (NLP) search capabilities to allow business users with average technical skills to gather and analyze data and achieve results. Without these simple tools, the enterprise cannot ensure user adoption of the solution.

Natural Language Processing Search Analytics (NLP) is crucial component to search analytics in that it allows business users to perform complex searches without endless clicks, coded queries, or complex navigation and commands. Users can access and view clear, concise answers and analysis quickly and easily, leveraging a familiar Google-type interface to compose and enter a question using common language.

Natural Language Processing and NLP Search Analytics Give Business Users True Access to Analytics

When you choose Augmented Analytics with machine learning and natural language processing (NLP), your users can enjoy a self-serve environment that is easy and intuitive, and will increase user adoption, data democratization, and return on investment (ROI).

NLP search technology significantly simplifies the user experience and encourages team members to learn and incorporate augmented analytics into their daily activities. Finding information is easy! Let’s suppose a team member wants to understand the trends in regional bakery sales. With NLP, the user can simply ask, ‘how many bakery products were sold in the Southwest and Southeast regions in 2023?’

Natural Language Processing (NLP) and search capability allows users to avoid scrolling through menus and navigation. The user only has to enter a simply worded search query, and the system will translate the query, and return the results in natural language using an appropriate form, e.g., visualization, tables, numbers or descriptions. There is no advanced training required. Users can analyze data and receive results in a way that is meaningful to them.

The benefits of augmented analytics using natural language processing (NLP) enable swift, easy searching and allows business users to create context-rich searches that provide in-depth information and concise results and can be used to solve problems, identify opportunities, spot trends and patterns and present data and recommendations. There is no need to request reports or information from IT, business analysts or data scientists. The business user has the tools and the capability to get results when and how they need the information.

‘Just a few years ago, Gartner predicted that, ‘50% of analytical queries will be generated via search, NLP or voice, or will be automatically generated.’ Today, this prediction is a reality.’

To find out more about Natural Language Processing (NLP), Machine Learning and NLP Search Analytics, Contact Us. Discover the power of Augmented Analytics, Machine Learning, and Natural Language Processing (NLP). Read our free article, ‘Why is Natural Language Processing Important to Enterprise Analytics?’

Original Post: Give Business Users NLP Search Analytics and Get Results!

Combine Mobile Analytics and Tally Solutions for Results!

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October 22, 2024

Integrate Tally with Mobile Analytics

Many small and start-up businesses have been using Tally Prime, Tally ERP and other Tally products for a long time. Their business users are familiar with the software and use it daily to manage all manner of financial issues, track, monitor, update and share information.

Today, business users are more mobile than ever before. Some work from home, some are on the road meeting with clients, customers and suppliers, and may be preparing for meetings or completing tasks in a hotel, airport or home office. In an environment where businesses are looking for a competitive edge, and trying to make the most out of precious resources, the use of mobile tools is more important than ever.

Every enterprise needs data and analytics to help team members make confident, fact-based decisions, but it can be difficult to get users to adopt these tools, especially if they see it as just one more thing they have to do, one more thing they have to learn! By integrating analytics with Tally solutions, and providing this integrated functionality in a mobile environment, the enterprise can encourage user adoption, and illustrate the value of analytics to its user base.

‘If you wish to integrate analytics with your Tally solution, choose a reputable, proven solution with a full suite of capabilities..’

Science Direct studied financial analytics and the use of tools to monitor, manage and find information. ‘Machine learning models do not make such assumptions. They are therefore more flexible and iterative. They are also able to model non-linear data.’

Discover the Power of Integrated Mobile Analytics and Tally Solutions

When you integrate mobile machine learning augmented analytics with Tally solutions, you can refine your understanding of issues and opportunities and make better decisions. There are numerous benefits to integrating analytics with the Tally environment, including:

  • Access to the familiar Tally environment using a native iOS or Android mobile app
  • Tally mobile analytics extends the office environment so users can perform crucial tasks from anywhere
  • Users have near real-time access to recent transactions and data
  • Mobile access provides an intuitive interface and navigation for clear analysis and results
  • Users can manage information for multiple entities and companies
  • Cloud server fetches and displays data, graphs and reports
  • All interaction and transactions are secured

If you wish to integrate self-serve analytics with your Tally solution, choose a reputable, proven solution with a full suite of capabilities. SmartenApps for Tally Mobile application is based on the Smarten Augmented Analytics suite of advanced analytics and is accredited by Gartner and recognized for its intuitive, easy-to-use analytics, Smarten offers stunning visualization, dynamic charts and graphs, modern business intelligence features, and key performance indicators (KPIs) metrics.

‘In an environment where businesses are looking for a competitive edge, and trying to make the most out of precious resources, the use of mobile analytical tools is more important than ever.’

Find out how mobile SmartenApps For Tally can your small business team and extend access to your Tally solution with analytics that offer accounting, finance, sales, inventory, and purchasing professionals and team members the tools they need to improve performance.

Integrate Tally with Mobile Analytics

Original Post : Combine Mobile Analytics and Tally Solutions for Results!

Auto Insights: The Secret Weapon for Analytical Results

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October 10, 2024

Auto Insights: Clear and Concise Analytics

Gartner predicts that ‘organizations that offer users access to a curated catalog of internal and external data will derive twice as much business value from analytics investments as those that do not.’ In order to make the most of the data that resides in all the corners of your enterprise, you must make sense of that data, and leverage it to create products and services, to compete in your market of choice and refine your workflow and tasks to improve productivity and agility.

The key to making the most of your data is analytics, and the ability to gather and analyze data and produce results that are intuitive and clear. Machine learning has evolved to support the average business user with tools and techniques that make it easier to gather and analyze data using simple techniques that are supported by analytical techniques, without requiring business users to have data science skills.

‘Auto Insights analytics allows business users to select the dataset to be analyzed, and let the system do the rest.’

Today’s business users expect to have access to software solutions and techniques that are easy to understand and navigate. As consumers, they have the world at their fingertips, with simple techniques that require little to no technical knowledge. If your enterprise plans to adopt augmented analytics tools and business intelligence techniques, it must provide simple tools that are easy enough for the average business users to incorporate into workflow and tasks. This approach will help the organization achieve its analytical goals while ensuring an appropriate return on investment (ROI) and decreasing Total Cost of Ownership (TCO). It can also encourage and enable Citizen Data Scientist initiatives and improve data literacy.

Business Users Can Leverage Auto Insights to Easily Analyze Data

The Auto Insights approach to analytics provides a foundation of Assisted Predictive Modeling and easy-to-use tools, making it simple enough for every business user to adopt as an important tool in the team toolkit, and supporting the path from business user to Citizen Data Scientist, with tools that encourage data literacy.

Auto Insights frees business users and reduces the time and skills required to produce accurate, clear results, quickly and dependably, using machine learning that frees the business user to collect and analyze data with the guided assistance of a ‘smart’ solution.

Auto Insights allows business users to select the dataset to be analyzed, and let the system do the rest. The tool will interpret the dataset, select important columns of data, analyze its type and variety and other parameters and then use intelligent machine learning to automatically apply the best algorithm and analytical technique and provide data insight so the user can easily see and understand the results.

The Auto Insights concept is applied to data repositories to enable the enterprise and its business users to perform complex data analytics and share analysis across the organization in a self-serve, mobile environment, bringing the power of sophisticated, advanced analytics and smart data visualization to the members to automate and analyze, so enterprise users can quickly get the answers they need and move on to make confident decisions.

‘The key to making the most of your data is analytics, and the ability to gather, analyze and view data easily, and produce results that are intuitive and clear.’

If you are interested in finding out more about the advantages of the Smarten Auto Insights approach to Augmented Analytics and self-serve search analytics, Contact Us to explore how these techniques can help your enterprise apply analytics to achieve results. Let us help you realize your business goals and objectives with fact-based information.

Original Post : Auto Insights: The Secret Weapon for Analytical Results

Understanding How Businesses Use Mobile BI to Achieve Results!

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October 2, 2024

Mobile BI Business Use Illustrates Real Advantages!

Mobile Business Intelligence (or Mobile BI) is defined as ‘a system comprising both technical and organizational elements that present historical and/or real-time information to its users for analysis on mobile devices such as smartphones and tablets (not laptops), to enable effective decision-making and management support, for the overall purpose of increasing firm performance.’

Aberdeen Group reports that businesses adopt Mobile BI to:

  • Improve business process efficiency
  • Improve employee productivity
  • Make better decisions, more quickly
  • Provide better customer service
  • Deliver real-time bi-directional data access to make decisions anytime and anywhere.

‘Mobile BI benefits go well beyond simple reporting and the sharing of data across user groups, to address real business issues and to keep users up to date and allow them to respond to real world, real-time issues.’

As local and global competition increases, most businesses are looking for ways to improve their competitive advantage, and to quickly adapt to the changing market, to employee needs and to customer buying behavior.

It can be helpful to consider some real-world business use cases, in order to understand the value and benefit of incorporating a Mobile BI solution within your technology landscape and your analytics approach.

The advantages of Mobile BI go beyond team collaboration and individual reporting needs, to provide the background and foundational information needed to make decisions on business strategy and to understand customer preferences.

Real World Business Use of Mobile BI Reveals Benefits and Advantages

The following list of companies represents a small sampling of businesses currently using Mobile BI to improve business results and efficiency:

Amazon – Amazon analyzes purchasing behavior and browsing history to predict what products a customer might want to see, and what they are likely to buy, personalizing the customer experience and making it easier for customers to complete a transaction. BI tools help the business to forecast demand and ensure that stock is available.

Starbucks – The business has implemented a loyalty program to help with customer engagement and sales, personalizing marketing strategies and allowing customers to order, pay and receive rewards. It gathers data using its digital channels and uses that data to create targeted offers and to improve customer retention, as well as increasing the amount customers spend during a visit.

Netflix – The company uses BI tools to personalize the viewing experience and to analyze customer viewing preferences and push specific options to the customer based on viewing history. Mobile BI tools allow teams to analyze and share information regarding regional viewing and to make decisions on the fly.

Uber – The company business model is dependent on the rapid changes and shifting behavior of customers from one local and regional area to the next. Real-time pricing and operational decisions are made to support surge pricing and driver deployment for high demand areas. The back-end systems and BI tools allow drivers to access information using the Uber app so that they can quickly respond to the changing environment.

Tesla – Mobile BI and wireless car data analytics allow Tesla to connect remotely to corporate offices and collect and analyze vehicle data to address issues and update customers on maintenance etc.

X/Twitter – Mobile BI provides support or moderators to identify and quickly address platform safety issues, violations, etc. The integration of artificial intelligence (AI) with BI tools allows the business to quickly respond and ensure a safe user experience.

Mobile BI provides the background and foundational information needed to make decisions on business strategy and to understand customer preferences.

These examples illustrate the many ways in which Mobile BI can be used to address business issues, providing user access and analytics for team members no matter where they are and how they need to use the data. Mobile BI benefits go well beyond simple reporting and the sharing of data across user groups, to address real business issues and to keep users up to date and allow them to respond to real world, real-time issues.

If you want to support your business user team and provide a foundation for BI tools that will better serve your team and your customers, explore Smarten Mobile BI benefits and features,  with powerful functionality and access for your business users including out-of-the-box Mobile BI and advanced analytics for every team member. For more information on Mobile BI and Augmented Analytics, read our article, ‘Understanding The Truth About Mobile BI.’

Original Post : Understanding How Businesses Use Mobile BI to Achieve Results!