We love DataBolt® so much, we use it to create & deliver our data products.

DIH works with a wide variety of data sources, file formats and end-user requirements. We need tools that enable us to quickly & easily pull in raw data, process it as needed (e.g. validate & clean raw data, munge data together, perform final quality checks) and deliver finished data files to end-users in various formats (e.g. CSV, XML, parquet, etc.) and via multiple methods (e.g. bulk file download, API). We use DataBolt® to complete all of these tasks.

DataBolt® accelerates your data science. Often the majority of time in data science is spent on tedious tasks unrelated to data analysis.  DataBolt® simplifies those tasks so you can quickly & easily get your data ready for analysis. 

Manage Workflows — With DataBolt® you can quickly build complex data science workflows:

• Build workflow with task dependencies and parameters
• Check task dependencies and their execution status
• Intelligently execute tasks including dependencies
• Intelligently continue workflows after changed/failed tasks
• SQL storage integration
• Dask and PySpark integration
• Automatically detect data changes
• Advanced machine learning features

Manage Data Sets — DataBolt® is a turnkey solution to host data files, documentation and metadata so others can quickly use your data:

• Quickly create public and private remote file storage
• Push/pull data to/from remote file storage
• Secure your data with best practice security
• Centrally manage data files across multiple projects
• Self-hosted remote storage
• On premises deploy
• Data encryption
• Data versioning

Ingest Data — With DataBolt® you can quickly & reliably ingest raw CSV, TXT and Excel® files to SQL, pandas, parquet and more:

•  Check and fix data schema changes
•  Fast writing from pandas to Postgres and MySQL
•  Ingest messy Excel® files
•  Out-of-core support
•  MS SQL integration
•  Advanced database features

Join Data — Easily join different data sets without writing custom code using fuzzy matches:

• Easily find join columns across data frames
• Automatic content-based exact joins
• PreJoin quality diagnostics
• Descriptive stats for id/string joins
• Join >2 data frames
• Automatic content-based similarity joins
• Advanced join quality checks
• Fast approximations for big data

DataBolt® Pipe — Make data delivery and on-boarding more efficient:

• Turnkey Infrastructure — Manage data files, documentation and meta data using flexible and secure infrastructure
• Simple Web GUI — Non-technical users from business teams can access and manage datasets without involving engineering teams
• Faster On-boarding — Data consumers benefit from unified delivery, richer meta data and fast access via free GUI, API and Python libraries
• Better Documentation — Richer meta data and documentation make it easier and faster to ingest, analyze and understand data

DataBolt® Difference — How DataBolt® is different from other tools and services:

• Open Architecture — Designed to promote data exchange to reduce frictions in data pipelines.
• Flexible Access — Use Python libraries, REST API or GUI - in cloud or on prem.
• Immediate Use — No lengthy sales process, technical setup or deployment.
• Community Enabled — Contributions from the community are welcome and encouraged.

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