Morgan Stanley 181010 - IBM Db2 Users groups in New York · Business Development, Emerging...

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IBM Cloud / © 2018 IBM Corporation Query anything, anywhere Query many data sources as one Data Virtualization Dave Williamson Business Development, Emerging Analytics Technology [email protected]

Transcript of Morgan Stanley 181010 - IBM Db2 Users groups in New York · Business Development, Emerging...

Page 1: Morgan Stanley 181010 - IBM Db2 Users groups in New York · Business Development, Emerging Analytics Technology dwilliamson@ca.ibm.com. ... mobile with advanced analytics using the

IBM Cloud / © 2018 IBM Corporation

Query anything, anywhereQuery many data sources as one

DataVirtualization

Dave WilliamsonBusiness Development, Emerging Analytics Technology

[email protected]

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IBM Cloud / © 2018 IBM Corporation

Data is Everywhere and increasingly heterogeneous

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IBM Cloud / © 2018 IBM Corporation

Performing Analytics Today

AnalyticsApplication

Data LakesData Warehouses

Data Marts

Costly and Complex

High Latency from source to use

Does not meet Business need

Compute resources at source not utilized

Error prone, data integrity challenges

Applications expect homogeneity

Not scalable

Not all data needs to be moved or copied

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IBM Cloud / © 2018 IBM Corporation

Resulting Data Architectures

Numerous ETLs

Unnecessary duplication, replication

Data governance issues accelerating

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What is Data Virtualization?

IBM Cloud / © 2018 IBM Corporation

The ability to view, access, manipulate and analyze data without the need to know or understand its physical format or location

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A new approach to Data Virtualization

Now in beta trial. Coming to ICP for Data in November

Queryplex service node

ServiceNode

Cluster

Constellation

Caching

Policy

Data SourceNode

AnalyticsApplication

Query anything, anywhere. Query many heterogenous data sources as one across cloud, on-premise and

mobile with advanced analytics using the

most popular languages and tools

Simplicity and scalability. Automatically discover, and connect

few to many devices and data stores into a single self balancing

constellation. Avoid the complexity of

centralized copies. Data only persists

at the source.

Execution speedup. Many times acceleration using

the power of every device to

compute and aggregate results.

Security. Fully secure and encrypted

communication and

preservation of data access

rights at source.

1

2

3

4

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What is fundamentally different?

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Classic Federation & Edge Computing

Querycoordinator

Query issued against the system

A coordinator receives the request and fans the work out to edge nodes

Edge nodes individually perform as much work as they can based on their own data. Individual results are sent back to the coordinator for final merging and remaining analytics.

Coordinator receives intermediary results from all edge nodes, merges results, and performs remaining analytics

Query Result

Query issued against the system

A coordinator receives the request and fans the work out to edge nodes

Edge nodes self organize into a constellation where they can communicate with a small number of peers. Nodes collaborate to perform almost all analytics, not only analytics on their own data.

Coordinator receives mostly finalized results from just a fraction of nodes. Completes the final work for the query result.

coordinator

New Computational Mesh

QueryQuery Result

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IBM Cloud / © 2018 IBM Corporation

Supported Languages & Data Sources

SQL (ANSI) ✓SQL (Oracle) ✓SQL (DB2) ✓SQL (PostgreSQL, Netezza) ✓Spark SQL ✓SQL Python ✓SQL in R & SparkR ✓PL/SQL (stored procedures) Future

SQL PL (stored procedures) Future

Oracle ✓ Excel ✓Db2 (software, appliance, cloud) ✓ CSV (delimited text) ✓Netezza ✓ Cloudera ✓PostgreSQL ✓ Teradata ✓Informix ✓ Db2/Z ✓MySQL ✓ MongoDB Future

SQLServer ✓ DVM Future

DerbyDB ✓ Redis Future

Big SQL ✓ Cloudant Future

Db2 Event Store ✓ Greenplum Future

Query LanguagesMix Any Combination of Data Sources

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ICP for DataUse Case: Manage All Your Data – regardless of where it lives

Governance of Consumers and ProducersWith lineage, context & metrics

End Users

App Developers

Data Engineer

Data Scientists

COMMENT

WORKSTREAM

PERSON

PERSON

DATASET

VISUALIZATION

APP

DATASET

INVOKES RESPONSE

USES

DATASETCOMMENT

WORKSTREAMMODEL

COMMUNITY

Structured & Unstructured Data

Public Cloud

On-Premises

Private Cloud

Your Data Anywhere

Business Analysts

IBM Data Virtualization

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http://[email protected]