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 data management tools that enable us to quickly and easily pull in raw data and process it. We use DataBolt® to complete such tasks as:
- Validate and clean raw data
- Munge data together
- Perform final quality checks
- Create final data files in various formats (e.g. CSV, XML, parquet, etc.)
- Deliver data to end-users via multiple methods (e.g. bulk file download, API)
Accelerate Your Data Science.
Often the majority of time in data science is spent on tedious tasks unrelated to data analysis. Instead of analyzing your data, you spend way too much of your time “making your data ready to use”. DataBolt® simplifies those tasks so you can quickly and easily get your data ready for analysis.
Quickly Build Complex Data Science Workflows.
With DataBolt® you can quickly build complex data science workflows. Use its python-based tools to:
- 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
DataBolt® is a Turnkey Solution.
DataBolt® is a turnkey solution to host data files, documentation and metadata so others can quickly use your data. With DataBolt® you can:
- 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
Ingesting & Joining Data is Simple.
With DataBolt® you can quickly and reliably ingest raw CSV, TXT, and Excel® files to SQL, pandas, parquet, and more. Complete such data tasks as:
- 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
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
Make Data Delivery and On-Boarding More Efficient.
DataBolt® Pipe makes delivering data to end-users and onboarding new data more efficient with such features as:
- Turnkey Infrastructure — Manage data files, documentation, and metadata using flexible and secure infrastructure
- Simple Web GUI — Non-technical users from business teams can access and manage datasets without involving engineering teams
- Faster Onboarding — Data consumers benefit from unified delivery, richer metadata, and fast access via free GUI, API, and Python libraries
- Better Documentation — Richer metadata and documentation make it easier and faster to ingest, analyze and understand data
DataBolt® is different from other tools and services in several ways:
- Open Architecture — Designed to promote data exchange to reduce frictions in data pipelines
- Flexible Access — Use Python libraries, REST API or GUI – in the cloud or on-prem
- Immediate Use — No lengthy sales process, technical setup, or deployment
- Community Enabled — Contributions from the community are welcome and encouraged