Agenda

• What is Big Data?

• Technology Radar

• Technologies in scope.

• Architecture

• Wanted!

• Next steps.

The world of data is changing.

Data has a chaotic nature.

Big Data <> Big DataBig Data == Big in Data.

Big Data = 4 V’s.

Volume = Dealing with the size.

Variety =

Handling the multiplicity of types, sources and formats.

Velocity=

Reacting to the flood of information in the time required by the application.

Veracity =

How can we cope with uncertainty, imprecision, missing values or untruths.

Big Data 1.0=

Building the capabilities to process large dataIn support of their current operations

(efficiency improvement).

Big Data 2.0=

What can I now do that I couldn’t do before, or do better then I could do before.

Polyglot persistence

• Relational databases are not dead.

• Enterprises should expect multiple data-storage technologies for different applications.

• Even for a single application, polyglot persistence is good.

• Do not replace one database solution with another to expect wonders.

Technologies in the picture

• Hadoop and technologies build on top of it.

• ElasticSearch.

• neo4J.

Hadoop

• Apache Foundation

• Commercial solutions

• Hortonworks

• Cloudera

• MapR

And many more...

ElasticSearch

• Based on lucene.

• ElasticSearch is also the name of the company.

• Search, analyze and index in realtime.

• Distributed.

• High availability.

• Document-oriented.

• Schema free

• RESTful api

neo4j

• Graph database.

• Ideal for metadata and relationships.

• Not for large content.

• Not for large graphs.

Polyglot persistence

• Relational databases are not dead.

• Enterprises should expect multiple data-storage technologies for different applications.

• Even for a single application, polyglot persistence is good.

• Do not replace one database solution with another to expect wonders.

Next steps.

Learning and case study group.

I need datastores:- Openstreetmap.- NASA- ....

Q&A