Versium now offers the following set of Open Source tools available to the public on GitHub:
Offline File Hasher - Try it Now!: this tool will hash (MD5, SHA1 and SHA256) all data fields in an input file locally on your machine. To download right-click this link and select "Save link as" to save the file as HTML locally on your device. Once downloaded, double-click on the Offline File Hasher to open it.
Lead Modeling and Scoring: a Python library and set of command line tools for the creation of lead scoring pipelines. The toolset simplifies the process of appending data across multiple APIs and then building lead scoring models that leverage both the original and appended data points.
Data Manipulation shell file tools: A collection of simple, fast, and efficient command-line tools for data manipulation. Below is the list of tools included:
- fld-ctr - Prints output with a field number prefixed to each field encapsulated in parenthesis.
- fslicer - "Virtually" slices a file on disk into X number of slices and outputs slice Y to standard output. Extraordinarily useful in parallel processing of a single large file.
- fwc - "Fast Word Count". Similar to "wc", this tool samples a file and makes a projection as to approximately how many lines are in the file.
- get-fs - Reads an entire file and builds a digest of fill rates and other summary stats.
- hashpend - Reads a hash table then builds keys from input records specified by fields on cmd line and appends any result to the end.
- rnd-extract - Randomly extracts n lines from a file. This is done using a specific seek and read mechanism that gives a true random sample of a file.
Treasure Box for Treasure Data: Treasure Box demonstrates how to leverage the Versium REACH APIs to retrieve third party data for consumers and businesses. This will allow access to all of the consumer and business data you need to integrate in your application development and enable your marketing to identify, understand and reach their ideal prospects.
The main Versium GitHub repository can be found on: https://github.com/VersiumAnalytics/