Reporting and Analytics with NoSQL
databases
ernesto ongaro - dublin
june 2013
Agenda
- What is NoSQL about?
- Explore 3 ways to get at your NoSQL data
- Indirect batch analysis
- Batch analysis
- Interactive exploration
- Example + Demonstration
- Q&A
Relational Databases
- Relational databases have their place in the world
- Databases are sets of tables, those tables have fields
- Data is stored in columns and rows
NoSQL Databases
Store data differently: documents, key value stores, graphs
source: rackspace
Why NoSQL?
- Scaling
- Simpler data model
- Volume (stream i/o)
- No schema
Reporting and Analytics?
-
Reporting is typically about filtering columns and rows and arranging them how you want the data to be displayed
-
Analytics is typically about aggregating the data in those rows and visualizing it in a crosstab or chart
this is true for both NoSQL and SQL data
exceptions: graph and tree visualizations and other specialized visualizations
So....
The labor of reporting and analytics on NoSQL is "flattening" data and fitting it into rows and columns
3 Ways to get at your NoSQL data
Indirect Batch Analysis
-
Benefits:
- Use your BI tool of choice
- ETL lets you "clean" data which is most important
- Down falls:
- Latency and maintenance of ETL process
- Making copy of data
Interactive Data Exploration
- Benefits:
- No latency
- No development of ETL
- Downfalls:
- Data quality issues
- No metadata, queries still written by developers
Direct batch reporting
- Benefits:
- Leverage native query language
- Low/No latency
- Downfalls:
- No data quality filter
- Queries on NoSQL can be hard (no joins, etc)
Jaspersoft:
Does all three!
Direct batch and Live exploration connectors for:
MongoDB, Cassandra, Hadoop Hbase, VoltDB, Neo4J
ETL components (from Talend):
-
Demo on MongoDB Reporting
- Demo on data MongoDB Exploration
Questions?
Thank you!
@not_a_poet
Reporting and Analytics with NoSQL databasesernesto ongaro - dublinjune 2013
By ernestoo
