Vedics has carved a niche in offering business oriented Knime Analytics services for elite organizations and enterprises across diverse business domains. Vedics provides spectrum of solutions which fit to any size of organizations. We create a roadmap and holistic approach to our client requirement and provide unique solution as per your business requirement.

What is Knime?

KNIME Analytics Platform is the open source software for creating data science. Intuitive, open, and continuously integrating new developments, KNIME makes understanding data and designing data science workflows and reusable components accessible to everyone.

Features of Knime

Import Data from any Source

Open and combine simple text formats (CSV, PDF, XLS, JSON, XML, etc), unstructured data types (images, documents, networks, molecules, etc), or time series data.

Connect to a host of databases and data warehouses to integrate data from Oracle, Microsoft SQL, Apache Hive, Snowflake, and more. Load Avro, Parquet, or ORC files from HDFS, S3, or Azure.

Access and retrieve data from sources such as Salesforce, SharePoint, SAP Reader (Theobald Software), Twitter, AWS S3, Google Sheets, Azure, and more.

Manage your Data in Various Ways

Derive statistics, including mean, quantiles, and standard deviation, or apply statistical tests to validate a hypothesis. Integrate dimensions reduction, correlation analysis, and more into your workflows

Aggregate, sort, filter, and join data either on your local machine, in-database, or in distributed big data environments.

Clean data through normalization, data type conversion, and missing value handling. Detect out of range values with outlier and anomaly detection algorithms.

Extract and select features (or construct new ones) to prepare your dataset for machine learning with genetic algorithms, random search or backward- and forward feature elimination. Manipulate text, apply formulas on numerical data, and apply rules to filter out or mark samples.

Visualize and Share your Data Insights

Visualize data with classic (bar chart, scatter plot) as well as advanced charts (parallel coordinates, sunburst, network graph, heat map) and customize them to your needs.

Display summary statistics about columns in a KNIME table and filter out anything that's irrelevant.

Export reports as PDF, PowerPoint, or other formats for presenting results to stakeholders.

Export reports as PDF, PowerPoint, or other formats for presenting results to stakeholders.

Case Study

Reducing Human Error by Automated Invoice Checking Process

In any business for recording financial transactions, Accounting is very important. It provides crucial information about the business like profit, loss, liabilities, and assets for decision-making, and planning. So it is an important part of business it should be optimized so it will reduce time, reduce human error, and enhance quality

We receive more than 100 invoices from our vendor every month. All invoices are checked manually because there is no automated process to check these invoices, these tasks are very time-consuming and there is always a possibility of human errors. To avoid all these issues in invoice checking we are using the KNIME Analytics Platform.

Steps in KNIME Analytics Platform

  • Invoice files should be transformed in order to extract dates in a proper format.
  • Database data should be filtered by respective month and vendor.
  • Match the data from both sources in order to find the same data (using the Joiner, Rule Engine, and Group By nodes)
  • Check if there is any missing data.


A report with relevant data is delivered after project completion. It provides a clear overview of the invoicing data from the selected partner. The other benefits of this project are:

  • Reduced costs and time due to automated invoice processing
  • Eliminated the human error possibility
  • We can detect if there are any inconsistencies between the database and invoices in the early stages.