DataStax: Making a Difference with Smart Analytics

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Most enterprises jumping onto the Big Data Analytics bandwagon are trying to build an hammer and then look for nails to hit. Unfortunately offerings from competing vendors within the analytics space encourages the one-size-fits-all mindset. This talk drills into how to use DSE Analytics to create smart analytically-driven applications that delight customers and deliver the information needed by enterprises to make smart business decisions.

Technologie

DataStax Enterprise: Making a Difference with Smart Analytics

1 DataStax Enterprise Platform Overview
2 Why DSE Analytics?
3 DSE Analytics Portfolio
4 Spark / C* to nail Operational Analytics
5 Use Cases
6 Conclusion
2© 2015. All Rights Reserved.

DataStax Enterprise - Platform Overview
© 2015. All Rights Reserved. 3

Why DSE Analytics?
© 2015. All Rights Reserved. 4
OLTP OLAP
2000's

Why DSE Analytics?
© 2015. All Rights Reserved. 5
OLTP OLAP
Web, Mobile, IoT

DataStax Enterprise Analytics Portfolio
© 2015. All Rights Reserved. 6
Streaming NRT Analytics Warehousing

DSE Analytics: Spark + Cassandra
© 2015. All Rights Reserved. 7
Spark Core Engine
Spark SQL Spark
Streaming
MLlib GraphX Spark R
Cassandra / DataStax Enterprise
DataStax Spark-Cassandra Connector

Operational Analytics: Spark and Cassandra
© 2015. All Rights Reserved. 8
Stream
Processing
Reliable Data
ingestion
Low Latency
Lookups & Search
Data @ Rest
Analytics
Ecosystem
Integration
ODBC
JDBC
BYOH
DataStax Enterprise Analytics

DSE Analytics Use Cases
•  Internet of Things
–  Cassandra can ingest all the events
–  Spark / Search to analyze
–  Spark Streaming for “standing queries” and rollups
–  Example:
•  Fraud
–  Bring together batch and real-time analytics for ensemble learning to
detect sophisticated fraud quickly
–  Post trade surveillance for risk and regulatory compliance
–  Example:
© 2015. All Rights Reserved. 9

Conclusion
© 2015. All Rights Reserved. 10
•  Foundational block for Web, Mobile, IoT
•  Operational backbone (not a data warehouse)
•  Backing of DataStax Enterprise Platform

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DataStax: Making a Difference with Smart Analytics

1. DataStax Enterprise: Making a Difference with Smart Analytics

8. Operational Analytics: Spark and Cassandra © 2015. All Rights Reserved. 8 Stream Processing Reliable Data ingestion Low Latency Lookups & Search Data @ Rest Analytics Ecosystem Integration ODBC JDBC BYOH DataStax Enterprise Analytics

9. DSE Analytics Use Cases •  Internet of Things –  Cassandra can ingest all the events –  Spark / Search to analyze –  Spark Streaming for “standing queries” and rollups –  Example: •  Fraud –  Bring together batch and real-time analytics for ensemble learning to detect sophisticated fraud quickly –  Post trade surveillance for risk and regulatory compliance –  Example: © 2015. All Rights Reserved. 9

11. Thank you