OTHER DATA PROTECTION CASE STUDIES
Customer is a leading Personal Data Privacy and Protection provider.
It enables advanced machine learning and identity intelligence to help enterprises better protect their customer and employee data at petabyte scale.
It identifies all PII across structured, unstructured, cloud & Big Data.
Customer demanded a connector app to integrate their platform with google big table. Connector app will parse data from big table and normalize it in the required format.
Spark SQL brings native support for SQL to Spark and streamlines the process of querying data stored both in RDDs (Spark’s distributed datasets) and in external sources. Spark SQL conveniently blurs the lines between RDDs and relational tables.
Google Big-table is a non-relational, distributed and multidimensional data storage mechanism built on the proprietary Google Storage technologies for most of the company’s online and back-end application/products. It provides scalable data architecture for very large database infrastructures.
Sacumen developed the connector app to integrate data store using java. The connector app performs the following actions:
Set up the prerequisites
Setup Google Big Table Developer login
Create Big Table instance on google cloud.
Or Big Table store with credential
Authentication is done by JSON file, which you can create and download from google cloud account.
Collect the schema/table information to scan
Normalize the data.