The Ingestion phase results in extremely large data sets ingested and stored into the Big Data structures and linked to other internal and external data sets. Large data sets captured pose few major challenges:
Large data sets come in different types and formats: structured and unstructured, data from conventional databases, documents, emails, videos, biometrics…
Data flows in highly inconsistent volumes and peaks. Capturing, merging and managing content varieties pose a high technological challenge in preparing and organizing Big Data for analysis
A Big Data storage platform should comply with the 5 “V”s to handle very large Volumesrequiring adequate automation to obtain better insights, within a Variety of types and formats requiring advanced connectors and adaptors. In addition, overcome the technological challenges caused by the Velocityof data flowing in different peaks, while ensuring its Validityremaing. Volatility, on the other hand, is the most important factor in order to understand what data is out there and for how long the data need to “live” to satisfy the needs of an organization, which can help in defining retention requirements and policies for Big Data Storage.
For Business Users
Supports a variety of types and formats through advanced connectors and adaptors for the Ingestion Phase
Ensure greater and centralized control over your data and projects
For The IT Department
Overcome high technological challenges related to the ingestion and validation of incoming data
Provide reliable data with embedded data processing for removing duplicates, fixing partial entries, eliminating null entries, aggregating results …
For the Corporate Strategist
Provide adequate automation in order to obtain better insights and views of the managed data
Understand what data is out there and for how long it needs to “live” to supporting in the definition of retention requirements and policies for Big Data
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