Author: Smarten

Low-Code and No-Code Development in Analytics!

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January 6, 2025

Using LCNC in Augmented Analytics

Low-Code Development and No-Code Development have been getting a lot of press in technology publications and conferences of late. If you are interested in finding out more about this topic, and about how low-code, no-code (LCNC) can be used to enhance analytics and change the approach of the self-serve, augmented analytics market, this article will provide you with a primer.

‘Including the LCNC approach in BI and analytics tools can and will support the enterprise as it moves forward, and can provide advantages and support for the future.’

Let’s begin with a Definition Of Low Code And No Code, and a discussion of the difference between Low Code And No Code Development.

What is Low-Code, No-Code Development and How Is It Used in the Analytics Market?

 

Low-Code Development

Low-Code Development allows programmers and developers to quickly and easily create applications using tools that simplify the development process with drag and drop components that enable the team to add features without writing code ‘from scratch.’ This visual development approach uses a graphical user interface (GUI) to support programmers as they build applications. To understand how this benefits the development team and the business, it is important to understand how low code platform works. By enabling swift development and mitigating the use of complex code, developers can easily add features to keep pace with the market and customer needs, so upgrades and iterations are fast and easy. The low-code platform is easy to integrate with existing systems, so it will support users of popular and familiar solutions with new features that are easy to use.

No-Code Development

No-Code Development requires no coding and is used to create simple, basic applications that can be quickly deployed and upgraded. The no code environment uses a graphical user interface (GUI) that is user-friendly and easy for developers to navigate. It supports developer productivity with easy-to-use tools and is less expensive than the typical software development approach, and it is easy to customize, though it is not scalable for complex application development and will produce only limited functionality. The no-code platform is fast and easy to use and provides an additional set of tools and an approach that will support programmer productivity and get products and upgrades to market quickly.

When considering the difference between low code and no code development, here is the bottom line:

Low-Code solutions use visual development environments and automated links to back-end systems, databases, web services and APIs.

No-Code solutions utilize visual drag-and-drop interfaces and require no coding, but rather are configured and implemented quickly, using the skilled application of tools and techniques.

The top low-code platforms are easy for developers to learn and the no-code environments have a library of pre-built components from which the team can choose.

World-renowned technology research firm, Gartner, predicts that low-code development tools will account for 75% of new application development by 2026. This prediction is primarily based on what Gartner perceives as increasing pressure for businesses to adapt quickly to market and competitive trends and changes.

The global technology research firm, Forrester highlights the complexity of existing technology environs, and the importance of supporting the business with agile, adaptable tools and workforce and suggests that low-code/no-code development allows organizations to accelerate innovation and increase business agility and sustainability.

Given the recent elevated status of low-code no-code in development and low-code no-code tools, it is important to consider whether the market has responded by adopting these techniques.

According to SlashData the use of LCNC has increased from 46% to 57% over a period of eighteen (18) months, with the usage of LCNC tools estimated at:

70% Data Science

66% Machine Learning

75% Embedded Software

69% Apps and Extensions for 3rd party ecosystems

58% Mobile Apps

Many businesses have employed LCNC to step up their competitive positioning and create and innovate quickly. Examples Of Low Code And No Code Business Innovation Include Amazon, Google, Apple, Akkio, DataRobot, and Microsoft.

When we consider the use of LCNC in business intelligence (BI) tools and predictive analytics, the reason for the uptick in usage among developers and IT professionals is quite clear.

As businesses embrace data democratization and recognize the need for data literacy among team members, and as enterprises launch Citizen Data Scientist initiatives, they face numerous obstacles and challenges, including the selection of an intuitive, self-serve BI and augmented analytics solution. Finding and choosing the right solution will drive willing user adoption, improved Return on Investment (ROI) and low Total Cost of Ownership (TCO).

But the selection of the right BI and analytics solution must also include considerations for sustainability, keeping pace with team, customer and market trends and changing behaviors, and ensuring that the technology investment will serve the organization in the long term.

Including the LCNC approach in BI and analytics tools can and will support the enterprise as it moves forward, and can provide advantages and support for the future.

For a more detailed discussion of Low-Code/No-Code in Analytics, explore our complementary article, ‘The Use And Benefits Of Low-Code No-Code Development In Business Intelligence (BI) And Predictive Analytics Solutions.’

Including the LCNC approach in BI and analytics tools can and will support the enterprise as it moves forward, and can provide advantages and support for the future.’

Contact Us to find out how no code data analytics and the low code approach for business analytics can support your needs. Our Business Intelligence And Augmented Analytics solution can help your business achieve objectives. Read this free article to discover the potential of no code business intelligence software and LCNC And AI In Predictive Analytics, explore our seamless Analytics Solution Technology.
Download A Free Trial Of Smarten Analytics Software.

For a detailed discussion of Low-Code/No-Code in Analytics, explore our complementary article, ‘The Use And Benefits Of Low-Code No-Code Development in Business Intelligence (BI) and Predictive Analytics Solutions,’ ‘How Does LCNC Enhance BI and Predictive Analytics,’ ‘Choose the Right LCNC BI Tools and Predictive Analytics,’ and ‘LCNC Benefits Teams, Business Users and Citizen Data Scientists.’

Original Post: Low-Code and No-Code Development in Analytics!

The Brave New World of Embedded BI and Embedded Analytics!

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January 2, 2025

Embedded BI: The New Secret Weapon

Your business users probably have their favorite legacy systems, best-of-breed solutions, and business apps. When your IT and management team introduce a new software application, it can often be seen as a nuisance or, at best, a tool whose day-to-day workflow value is not offset by the task of learning how to navigate the software.

Embedded BI is gaining in popularity, simply because it adds so much value to the organization and, with proper planning, it will also add immeasurable value to your team members.

‘With Embedded BI, users can achieve clear insight into data and improve the quality of decisions, present data in a clear fashion and achieve faster, more reliable results.’

Based on a recent survey, 49% of companies have increased their utilization of business intelligence analytics compared to pre-pandemic levels. That is an impressive statistic but it does not reflect the probability of user adoption and, without user adoption, the BI tools will reap very low return on investment (ROI).

Embedded BI Improves User Adoption AND Enterprise Market Targeting

In order to achieve the maximum value, the enterprise must choose a business intelligence and augmented analytics tool that is easy for users to embrace – one that provides clear visualization and results so users can present data, share data and understand results In a way that is meaningful to their role. With the right embedded BI tools, the organization can embed analytics within its most popular enterprise apps so users can make data-driven decisions.

The Embedded BI approach lends itself well to many business functions, i.e., inventory demand planning, customer relationship management (CRM), enterprise resource planning (ERP) systems, and many other functions. Industries like healthcare, research, financial services and others can leverage embedded BI to identify trends, patterns, issues and opportunities without the help of a programmer or IT specialist. The enterprise can embed analytics to improve the products and services they offer their customers. HR departments can identify demographics, workforce requirements, training needs, and more.

Business User Benefits

  • Users can see, gather and analyze data working within a single sign-on environment, eliminating the frustration of system silos and data migration.
  • Team members will be more productive, and the enterprise can improve workflow and make the users more efficient by saving time and eliminating redundancies and delays.
  • Users can achieve clear insight into data and improve the quality of decisions, present data in a clear fashion and achieve faster, more reliable results.

Enterprise Benefits

  • The business can optimize its staff and team by using their time more efficiently.
  • The organization can establish and use visualization formats and techniques that provide real value to the management team and the staff.
  • The enterprise can leverage tools to query data across various types of data sources, and to encourage collaboration.
  • With the right embedded BI and analytics solution, the organization can ensure mobile access to data, improve business processes using cutting-edge artificial intelligence (AI), and ensure appropriate security and user-friendly tools that will encourage user adoption and improve return on investment (ROI) and total cost of ownership (TCO).

Embedded BI is gaining in popularity, simply because it adds so much value to the organization and, with proper planning, it will also add immeasurable value to your team members.

You can find out more about the Smarten Embedded BI And Integration APIs solution and add powerful functionality and access to existing ERP, SCM, HRMS, CRM or any other products. Provide analytics capabilities within existing products without major Investment. Your business users and your customers will appreciate the ease-of-use and access and you will gain a competitive advantage. Read our White Paper: ‘Making The Case For Embedded BI And Analytics.’

Original Post : The Brave New World of Embedded BI and Embedded Analytics!

BI Reporting Tools Can Make or Break Decision-Making!

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December 17, 2024

Choose a BI Reporting Tool that Tells You What You Need to Know!

The ideal business intelligence and analytics solution includes traditional BI features, modern BI and analytics components and a full suite of reporting capabilities that are easy for your team to use, and will produce clear, concise results for fact-based decision-making.

According to a recent TechJury survey:

  • Data analytics makes decision-making 5x faster for businesses.
  • The top three business intelligence trends are data visualization, data quality management, and self-service business intelligence (BI).
  • 7 out of 10 business rate data discovery as very important.

‘A BI reporting tool that enables users to customize their view and approach and is easy to understand and use will make the user more productive and ensure Return on Investment (ROI).’

If you are considering a Business Intelligence or Augmented Analytics solution, be sure to select a software suite that provides your business users with personalized dashboards, multidimensional key performance indicators, and KPI tools, report software, Crosstab and Tabular reports, GeoMaps and deep dive analytics with 100% browser based interface and self-serve features that encourage and support Social BI and collaboration.

Select a Business Intelligence (BI) Reporting Tool That is Flexible, Agile and User-Friendly

By providing your team access to flexible, agile reporting tools, you increase the probability of user adoption, and improve the outcome, with reports and results that are meaningful to the user, and to the target audience of a presentation or distributed report.

Every business has unique reporting and documentation needs. Whether you are a business user or an analyst or IT professional, you use augmented analytics and BI tools in a way that is meaningful to your role. Gathering, preparing and analyzing is important but the final step in this process is equally important and that task often frustrates the user more than anything. Excel, cross-tab and tabular reporting are helpful, but those report and documentation options typically present data in columns and rows. A BI reporting tool that enables users to customize their view and approach and is easy to understand and use will make the user more productive and ensure Return on Investment (ROI).

Consider a Business Intelligence reporting tool that enables report, template and document design and configuration and supports preprinted fixed formats too. IT team members or consultants can leverage a simple, basic programming or scripting environment to define format templates and use data from Datasets and objects to produce stunning pixel perfect reports. Users can preview reports, export data to PDF files and share documents and reports via email at predefined frequency using delivery and publishing agents.

Benefits of Agile, Flexible Business Intelligence Reporting

  • Customize and Format Reports, Documents, Forms and Templates Using Basic Scripting Skills
  • Generate Reports from BI Datasets in Predefined Formats
  • Satisfy Unique Business, Departmental, Functional and Statutory Requirements
  • Present Information in a Clean, Attractive Format for Customers, Partners, Suppliers, Team Members
  • Allows Business Users to Gather, Present and Share Information via Email and Publishing Agent

‘If you are considering a Business Intelligence or Augmented Analytics solution, be sure to select a software suite that provides your business users with personalized dashboards, multidimensional key performance indicators, and KPI tools, report software, Crosstab and Tabular reports, GeoMaps and deep dive analytics.’

For out-of-the-box reporting and flexible, interactive formats, explore our full suite of reporting tools: Pixel Perfect Print Reports, Business Intelligence Reporting. If your organization is looking for BI Tools and Augmented Analytics that leverage advanced techniques to keep pace with changing enterprise needs and support business agility, let us help you realize your business goals and objectives with fact-based information, and flexible, scalable technology solutions that will support Citizen Data Scientist initiatives, and improved data literacy and data democratization.

Original Post : BI Reporting Tools Can Make or Break Decision-Making!

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!