Peliqan feature list

Peliqan provides an innovative user interface for busy data engineers and business teams to work with their company data in a spreadsheet-like environment. Working with data becomes as easy as working with a spreadsheet: filter data, add your own columns, apply transformations, make calculations and combine data, all in one intuitive interface.

Peliqan is powered by a unique federated query engine that enables “SQL on anything”, including all of your databases, data warehouses and even on real-time data from your SaaS business applications. The federated query engine also allows you to combine data across sources and even apply fuzzy joins.

Peliqan comes with a range of database connectors such as MySQL, Postgres, SQL Server and other databases on request.

Peliqan comes with a range of data warehouse connectors such as Snowflake, Redshift, BigQuery and others on request.

Peliqan can connect to SaaS business applications and fetch data in real-time. All SaaS data is converted into virtual tables that can be used in Peliqan as any other database table.

Peliqan can connect to SaaS business applications and sync data into its built-in data warehouse, in order to perform SQL queries on full datasets. All data from your SaaS applications is synced and remains up-to-date with the source.

Peliqan can connect to your on premise data sources through a secure VPN tunnel.

Peliqan automatically discovers the schema of each connected source.

Each table in Peliqan is fully editable as in a spreadsheet, including editing data, making corrections, adding columns, adding rows (new records), apply formulas etc. However, all changes are stored in virtual copies of the data that remain up-to-date with the source. Business teams can work with the data, make it their own, and all that is needed is a read-only connection to each source.

Add columns with formulas to any table, in order to make calculations and to apply transformations on data. Peliqan reduces the complexity of data transformations to working with formulas, similar to spreadsheets.

Thanks to the Peliqan federated query engine, all company data can be accessed not only as editable tables, but also through SQL queries. Power users can write queries that combine data from any source, including SaaS business applications. The resulting models can be shared as virtual tables with business users.

The Peliqan join, aggregation and union editor helps business users to combine and aggregate tables without the need to understand SQL.

Fuzzy joins allow users to combine data from different sources, even when there is no common key available. Fuzzy joins can be combined with transformations (e.g. applied as formulas) to merge datasets, for example merging customer data from a CRM with support tickets from a helpdesk database.

The aggregation editor in Peliqan helps business users to group data and calculate aggregations, without the need to understand SQL.

Peliqan has a built-in low-code app builder that can be used to build data-driven internal apps with data visualizations, interactions and the ability to make selective data updates.

You can build for example a tailored front-end for logistics partners to access data, flag shipments as complete, update stock etc.

Add charts to tables including pie charts, bar charts, line charts etc.

Materialize any table or query in Peliqan’s built-in data warehouse or your own DW.

Peliqan comes with a built-in data warehouse that is used to materialize tables & queries, and to store SaaS data sources.

You can also connect your existing data warehouse and let Peliqan materialize into your DW.

Peliqan’s low code Python scripting environment provides unified data access to writeback to SaaS source and implement reverse ETL.

The Peliqan connector builder is a comprehensive visual environment to build out ETL and writeback connectors to SaaS applications.

Peliqan offers a connector builder service or customers can build and test their own private connectors.

Peliqan visualizes the data lineage on both a table and column level in order to understand provenance of data, data dependencies and impact of making changes to existing virtual tables.

Peliqan allows to catalog data assets by adding metadata such as table and column descriptions, tags, owners etc.

Implement data contracts in YAML and check data sets for compliance using low-code scheduled scripts.

Implement data quality checks and scheduled monitoring on datasets using low-code scripts. Send out alerts to e.g. Slack to keep teams informed.

Implement data masking to mask sensitive data such as PII using low-code Python scripts.