Zap Data Hub Features

Reports interface for standard and self-service reports is intuitive and easy to use.

Requires a minimal number of steps/clicks to answer business question.

Offers a variety of attractive graph and chart formats.

Score cards visually track KPI's.

Provides business users an interface to easily design, refine and collaborate on their dashboards

Using formulas based on existing data elements, users can create and calculate new field values.

Business users have the ability to filter data in a report based on predefined or automodeled parameters.

Users can drill down and explore data to discover new insights.

Ability to search global data set to find and discover data.

Ability for users to share data and reports they have built within the BI tool and outside the tool through other collaboration platforms.

Tool automatically suggests data types, schemas and hierarchies.

Converts data formats of source data into the format required for the reporting system without mistakes.

Ability to (re)structure data in a manner that allows extracting insights fast and accurate.

Provides business users an interface to easily design and refine their dashboards and reports. (What You See Is What You Get)

Application Programming Interface - Specification for how the application communicates with other software. API's typically enable integration of data, logic, objects, etc with other software applications.

View ETL process data via reports and visualizations like charts and graphs.

Record ETL historical data for auditing and potential data correction needs.

Extract data from the designated source(s) like relational databases, JSON files, and XML files.

Cleanse and re-format extracted data to the needed target format.

Load reformatted data into target database, data warehouse, or other storage location.

Arrange ETL processes to occur automatically on needed time schedule (e.g., daily, weekly, monthly).

Capable of scaling processing power up or down based on ETL volume.

Automatic creation and management of documents.

The software supports a wide variety of data sources and data warehouses that require automation.

Supports a template system, making it easier to set up configuration parameters.

Consolidates, Cleanses and Normalizes data from multiple disparate sources.

Helps save storage capacity and improves query performance.

Eliminates data inconsistency and duplications ensuring data integrity.

SQL based analytics functions like Time series, pattern matching, geospatial analytics etc.

Provides built in capabilities like machine learning algorithms, data preparation functions, model evaluation and management etc.

Allows data querying across data formats like parquet, ORC, JSON etc and analyze complex data types on HDFS

Integrates with data science workflows, Machine Learning and artificial intelligence (AI) capabilities.

Integrates with BI Tools to transform data into Actionable Insights.

Provides On-Premise deployment options.

Provides Cloud deployment options (private or public cloud, hybrid cloud).

Manages huge volumes of data, upscale or downscale as per demand.

Policies, procedures and standards to manage and access data.

Restricts data access at a cell level, mask or hide parts of cells, and encrypt data at rest and in motion

Software is able to alert the user in case of any errors.

Utilizes data to proactively identify IT issues.

Creates new or streamlines existing data models to ensure business continuity.

Automates all parts of the Data Warehouse lifecycle - warehouse design, provision data sources.

Supports real-time data ingestions and updates in the cloud or on-premises.

Software delivers insights into data in order to identify gaps, risk within the data warehouse.

Supports no-code/low code development patterns.

Allows users to generate text based on a text prompt.

Condenses long documents or text into a brief summary.

Anticipates needs and offers suggestions without prompting