ConverSight Demystified 1
NLP/ NLQ for talking to your data
ConverSight ~ ConverSight Demystified Empowering business leaders with generative Al and augmented analytics. Whitepaper
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I. Introduction 1. What is ConverSight? ConverSight is a no-code, low-code integrated Augmented Analytics platform that empowers organizations to make data-driven decisions. It is a comprehensive solution that offers a wide range of functionalities, including Business Intelligence (Bl), augmented and predictive analytics, and planning capabilities. The platform provides real-time, vo ice-activ ated reporting, dashboards, alerts, and monitoring, allowing users to access and analyze data in a more efficient and convenient manner. One of the key differentiators of ConverSight is its ability to combine the features of traditional Bl analytics with the benefits of Machine Learning (ML) capabilities. The platform includes a Data and Al Workbench, which enables data engineers and machine learning engineers to configure their own tasks and flows, providing more flexibility and customization in data analysis and model development. Additionally, ConverSight includes embedded Machine Learning Operations (MLOps) function ality, which streamlines the deployment and management of machine learning models. Data Lake � � ffi m .,I� m m f [� � ➔ 0 2: " a m A"l:r � m l G • m C □ □ • -�- . □ □ • □ 0 • Transform & Aggregate � Al WorkBench § Ba o - 0 Datamart 0 0 0 \( 0 0 0 Knowledge Graph . o. • o . •o o • o ·o . . o • • . Mobile Application ➔ Embeddable Business Insights Web Appl!cation ConverSight also offers a vari ety of features that enable users to gain Insights from their data, such as advanced analytics and reporting capabilities, customizable dashboards, and the ability to create adv anced analytics apps. These features provide users with a comprehensive view of their data, allowing them to make informed decisions and optimize their operations. Power Bl, Tableau, and Qlik are popular Bl and data visualization tools, but they lack the ability to perform advanced analytics and ML tasks. ConverSight, on the other hand, offers a unique combination of Bl analytics and ML capabilities. Users can access real-time data, create interactive dashboards, and perform advanced analytics tasks, all within a single platform. www.conversight.ai
Athena Dashboards Control Tower CSApps Data Workbench Al Workbench www.conversight.ai Athena, the conversational Al analyst, enables users to ask questions about business data in natural language and receive answers. It operates on a patented technology that derives information from data through analyzing user queries. The Dashboards module enables users to create interactive visualizations and customized dashboards to monitor key performance indicators and make data-driven decisions. The module includes advanced data visualization and data exploration capabilities. The Control Tower module provides a centralized monitoring and management interface that offers real-time visibility into the performance and health of all analytics apps, flows, and infrastructure. It includes capabilities for monitoring key performance indicators, issue detection, and automated corrective actions. Additionally, it has alerts and monitoring functionality. CSApps is a feature that enables data engineers to build analytical applications that can be consumed by business users. By leveraging CS MLOps, these applications can be deployed in seconds and can be scaled quickly to meet the demands of a rapidly growing business. This eliminates the need for manual processes and allows for faster and more efficient decision making. The Data Workbench module provides a set of tools for data preparation, transformation, governance, and quality for data engineers. It also includes an interface for training the conversational bot (Athena) by defining and organizing data for Insights generation. The Al Workbench module offers a set of tools for data exploration,feature engineering, model development, and deployment for data scientists and machine learning engineers. It includes capabilities for creating and deploying machine learning models in a collaborative environment.
3. Advanced Data Explorer ConverSight provides businesses with a powerful set of tools for exploring their data and gaining valuable Insights from customer interactions. Our platform makes it easy for businesses to unlock the full potential of their data, with a range of advanced features that make it easy to explore and understand complex data sets. More Visual Options Pinning to the Dashboard Share with Internal and External Users Export to PDF and Excel www.conversight.ai Our platform provides businesses with more visual options for exploring their data, including a range of chart types, including bar charts, line charts, and scatter plots, among others. With the ability to view the same data in different chart types, businesses can gain a deeper understanding of their customer interactions and make data-driven decisions with confidence. With the ability to pin charts and reports to the dashboard, businesses can easily access their most important data, making it easy to stay on top of trends and Insights. Pinned charts and reports are always available, providing businesses with quick access to the information they need to make informed decisions. Collaboration and sharing is a critical component of any data-driven business and ConverSight makes it easy for teams to work together and achieve their goals. Our platform provides robust sharing features, allowing teams to easily share reports and Insights with one another, regardless of their location or role within the organization. The ability to share Insights and reports with stakeholders outside of the organization, such as customers or partners, helps to streamline workflows and improve outcomes. ConverSight provides businesses with the ability to export their charts and reports to PDF and Excel, making it easy to share data and Insights with stakeholders both inside and outside of the organization. Whether you need to share data with team members or present Insights to stakeholders, our platform makes it easy to share data and Insights with anyone, anywhere.
Overall, Control Towers offer a comprehensive solution for managing the complexities of the supply chain. With real-time visibility and advanced analytics, companies can make informed decisions, respond to disruptions proactively, and optimize their operations for maximum efficiency and success. 5. Analytical Apps for Actions and Recommendations - CSApps ConverSight builds analytical apps using an inbuilt feature called CSApps. These apps use the sophisticated platform and models to convey information visually and also helps in creating specific call to action capabilities. The framework's breadth allows for nearly unlimited application types. CSApps enables enterprises to easily access data analytics and machine learning Insights, and helps in creating quick deployable actions. This enhances decision-making, engagement, and competitiveness by making data more impactful and meaningful. With CSApps, organizations can create custom and brand-reflective apps for internal use, stakeholders, or public consumption, helping them to understand and interact with data, make informed decisions, and improve their overall performance. The Launchpad in ConverSight is a central area from which users can access all subscription-to resources. It provides a centralized location for launching the diverse tools, apps, and resources required to do various tasks. The Launchpad serves as a dashboard from which users may access the required resources without having to wade through multiple menus and submenus. It provides a simple and intuitive interface that enables users to quickly and efficiently access the required resources. Launchpad resources may include analytical apps, data visualization tools, and business intelligence dashboards in addition to process automation tools and collaboration platforms. The Launchpad is intended to give users with an effective means of accessing the resources they require to complete their task, thereby streamlining the process and enhancing Ill. ConverSight for Data Engineers 1. Data Ingestion Data Ingestion is an important step in the machine learning and analytics workflow, and it is essential for a successful outcome. In an automated ML studio like ConverSight, the process of data ingestion is streamlined and efficient. The following is a step-by-step guide to the data ingestion and preparation process in ConverSight: Data Connectors www.conversight.ai In the first step, data connectors are created to connect to various data sources. ConverSight supports a wide range of data sources including Excel, SQL, Oracle, Fishbowl, Shopify, SAP, HubSpot, Snowflake, and many others. Users can create connectors by specifying the connection details and authentication credentials for the data source. This is done by providing the necessary connection details such as server name, port, username, and password.
Define Tables and Columns Load Data into the Knowledge Base (KB) 2. Data Engineering Once the data connectors are created, users can define the tables and columns of the data source. This step involves selecting the relevant tables and columns that are needed for the analysis. Users can also define custom columns, rename columns, and perform other data preparation tasks. This is done by providing the name of the table, column names, data types, and other relevant information. After defining the tables and columns, the data is loaded into the KB. This step involves extracting the data from the data source, cleaning and transforming the data, and loading it into the KB for further analysis. This is done by using SQL commands or by using the provided U I interface to extract the data from the data source and load it into the KB. Data Engineering is a critical component of a data-driven company and an essential phase in the data analytics process. It entails extracting, processing, and loading into a consolidated data repository, which may then be utilized for data analysis and reporting. This stage is essential for ensuring that the data is cleansed, organized, and prepared for future analysis, resulting in accurate and insightful findings. A well-designed data pipeline guarantees that data is secure, consistent, and easily accessible to all stakeholders, so facilitating improved decision-making and, ultimately, enhanced business outcomes. The Data Workbench module is a comprehensive solution for data engineers, providing a range of tools for data connection, management, and governance. The module includes a set of tools that allow data engineers to shape, and transform data, preparing it for analysis. These tools include data merging, filtering, and aggregation, as well as data type conversion and text processing. Data Profiling Data Cleaning www.conversight.ai In this step, the data is profiled to understand the data quality, completeness, and integrity. This step is done by analyzing the data and identifying the data types, missing values, outliers, and other relevant information. This allows users to understand the data and identify any issues that need to be addressed. This step can also be done by using pre-built data profiling scripts or by using the provided U I interface to understand the characteristics of the data. Data cleaning is performed to remove any inconsistencies, errors, or outliers in the data. This step includes tasks such as removing duplicates, handling m1ss1ng values, and standardizing the data. This step can be done by using pre-built data cleaning scripts or by using the provided U I interface to clean the data.
Data Transformation Data Validation Data transformation is performed to restructure the data into a format that is more suitable for analysis. This step includes tasks such as filtering, pivoting, and aggregating the data. This step can be done by using pre-built data transformation scripts or by using the provided U I interface to transform the data. The final step in the data preparation process is data validation. This step involves validating the data to ensure that it meets the requirements for the analysis. This step includes tasks such as checking for data completeness and consistency, as well as ensuring that the data is in the correct format. This step can be done by using pre-built data validation scripts or by using the provided U I interface to validate the data. ConverSight also has a feature called "Data Lineage" that allows users to trace the data from its source to its final form, making it easy to understand the data and its quality. This feature also allows users to go back to the previous state of data and make any necessary changes if needed. Overall, the data ingestion and preparation process in ConverSight is designed to be efficient, user-friendly, and comprehensive. It supports a wide range of data sources, includes a set of pre-built data preparation and transformation recipes, has an intuitive interface for data preparation and data wrangling, and has the data lineage feature to help in understanding the data and its quality. The data ingestion and preparation process in ConverSight is designed to be efficient, user-friendly, and comprehensive. It supports a wide range of data sources, includes a set of pre-built data preparation and transformation recipes, and has an intuitive interface for data preparation and data wrangling. 3. Data Modeling The importance of effective data management cannot be overstated when it comes to developing Al applications. A well-designed data model facilitates the effective storage, retrieval, and processing of data, whilst proper indexing helps to provide quick and accurate search results. ConverSight is a premier Al platform with comprehensive data management features, such as data modelling and indexing. This section of the whitepaper will provide a full analysis of these characteristics and how they can benefit Al application developers and organizations. Train Athena(SME Coaching): The Train Athena option in the ConverSight platform is a key feature that allows organizations to train Athena to process their queries in the manner they prefer. This option provides a range of tools and capabilities that enable ad min to provide the necessary vocabulary, proactive Insights, and schema on their data to help the ML and Al model identify and process their queries accurately. One of the key benefits of the Train Athena option is that it allows organizations to customize the behavior of their conversational bot to meet their specific needs. One of the biggest benefits of ConverSight's data modeling is that it helps business users stay away from technical jargon and complex programming languages. With a well-designed data model, business users can easily understand and work with data, even if they have limited technical expertise. - 0 ...__,,· www.conversight.ai __:__
4. Data Science The Al Workbench module is a comprehensive solution for data scientists and machine learning engineers, providing a set of tools for data exploration, feature engineering, model development, and deployment. The module offers a wide range of tools and capabilities to help data scientists and machine learning engineers to work more efficiently and effectively. The Al workbench consists of Notebook, ML Studio, Tasks and Flows. Notebook Tasks www.conversight.ai The Notebook feature in the Al Workbench is designed to provide data scientists and data analysts with a flexible and powerful tool for data exploration, analysis, and visualization. The Notebook feature redirects users to the Jupyter Notebook server, which is a widely used and well-established platform for data science and machine learning. The Jupyter Notebook is a web-based interactive computing platform that provides a rich and interactive environment for data exploration and analysis. With the Notebook feature, users can access their imported data and interact with it in their preferred manner, exploring and visualizing their data to gain Insights and understand patterns and relationships. The Jupyter Notebook interface provides an intuitive and user-friendly way to work with data, with a range of tools and features that make it easy to access, manipulate, and visualize data. The Insights can also be imported to their dashboards. A "Task" is a fundamental building block in our platform that enables users to organize, store, and reuse code in a modular and efficient manner. It provides a convenient and flexible way for users to perform a single, related action, making it an essential tool for data scientists, data engineers, and other professionals working with data. A task serves the same purpose as a normal function in a programming language but is designed to be more flexible and accessible. The task is organized, reusable code that can be used to perform a specific action or set of actions related to data processing, manipulation, or analysis. The task is saved in the task library, which is a centralized repository of tasks that can be easily accessed and imported into the Notebook or ML Studio in the Al Workbench. This makes it easy for users to find and reuse tasks, reducing the time and effort required to develop new code and making it easier to collaborate and share code across an organization. The access to the task library is controlled by the task owner, who determines who can import and use the task. This enables organizations to maintain control over the code and data used in their projects, ensuring security and data governance. The
