SOLUTIONS

DATA CLOUD MOVEMENT

Leverage your data as a product

With Elisa Polystar’s cloud-native solution, you can collect, aggregate, consolidate, and mediate your data. Eliminate data silos by collecting, cleansing and bringing your data together from any source into a single, virtualized data pool.

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Data, like oil, is not useful in its raw state. Data Cloud Movement provides a productized, real-time data management platform that enables your teams and applications to use virtualized data assets without needing to know the technical details of how and where the data is stored. Streaming data can be ingested in multiple formats and is then refined, transformed, and stored in a common format in data sinks. Users can make the most of out of their data by running scheduled and ad-hoc queries on the data and by supplying their preferred business and analytics tools with batches of data. Data Cloud Movement helps operators to develop the structure their data needs to solve their specific use cases.

DATA CLOUD MOVEMENT PROVIDES DATAOPS AND DATA VIRTUALIZATION

Real-time ingestion

Data Cloud Movement can ingest data in a real-time streaming fashion, as well as batch files and micro-batches.

Several data collection protocols

SFTP, API, ESB Interface, TCP Stream, JDBC/OBC are supported off-the-shelf. New data collection protocols can be implemented to complement the solution as per customer need.

Data (field) encryption

All sensitive and personal data within the platform is encrypted, hashed or anonymized at ingestion. The data will be de-anonymized outside the platform by the application which receives it. Solution supports several hashing algorithms such as SHA-245, MD5 and Blowfish.

Configurable pipelines

Data Cloud Movement provides an intuitive user interface for customers to add their own data sources, filter the data, and transform the data before pushing it to the desired destination.

Data tagging & enrichment

The solution supports data lookup queries from external sources to enrich the input data. Micro-batches are supported with real-time cache lookups.

Scalable system

The system is scalable from compact initial deployments and can also be expanded to support large volumes of customer data traffic. The user interface allows for easy scalability adjustments.

Off-the-shelf data transformations

Process pipelines refine the source data by applying various transformations and can save it in a common format in data sinks. A vast number of transformation functions are available, including various complex split, time, and combine actions.

Data anomaly detection

Pattern-based data quality checking during data ingestion and between each transformation process ensures data quality by enabling alerts in cases of anomalies.

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DATA CLOUD MOVEMENT DEMO