two keys to analytic success: cooperation, collaboration

The Briefing Room

Twitter Tag: #briefr

The Briefing Room

Welcome

Host: Eric Kavanagh

[email protected]


The Briefing Room

!   Reveal the essential characteristics of enterprise software, good and bad

!   Provide a forum for detailed analysis of today’s innovative technologies

!   Give vendors a chance to explain their product to savvy analysts

!   Allow audience members to pose serious questions... and get answers!

Mission


The Briefing Room

FEBRUARY: Analytics

March: OPERATIONAL INTELLIGENCE

April: INTELLIGENCE

May: INTEGRATION


The Briefing Room

Analytics

FROM THIS


The Briefing Room

Analytics

TO THIS


The Briefing Room

Analyst: Robin Bloor

Robin Bloor is Chief Analyst at The Bloor Group

[email protected]


The Briefing Room

!   The ParAccel Analytic Platform: analytic database, extensibility framework, on demand integration and integrated analytics

!   The Platform connects to existing infrastructures and industry standard BI tools

!   Last month Gartner included ParAccel in its Magic Quadrant for Data Warehouse Database Management Systems

ParAccel


The Briefing Room

John Santaferraro

John Santaferraro is the Vice President of Solutions and Product Marketing at ParAccel. Prior to joining ParAccel, Santaferraro was an independent industry analyst in the business intelligence and analytics market. Before that he developed and executed a vertical market strategy for Hewlett Packard's BI group, focusing on energy, communications, retail, healthcare and financial services; he was also instrumental in helping establish HP’s new BI business group with a combination of solutions, products and consulting. In 2000, John founded a marketing and sales consulting company, Ferraro Consulting, providing business acceleration strategy for technology companies.

ParAccel and Unconstrained Analy1cs Coopera1ve Analy1c Processing Takes Center Stage

Copyright 2013 ParAccel, Inc. 10 Confidential. Do not Distribute.

New Analy1c Requirements

Driving the Analy/c Revolu/on

Next Genera/on Analy/c Pla8orms

Speed Sophis1ca1on Interac1on

New Analy/cs

Descrip1ve Prescrip1ve Predic1ve

Preventa1ve

Big Data

Corporate Data Machine Data

Conversa1onal Data Open Source Data


ParAccel Enables Coopera/ve Analy/c Processing

Business Intelligence and Repor/ng Tools

Advanced Analy/cs

Analy/c Applica/ons

Machine Data

Opera/onal Data

3rd Party Info

Provider

Streaming Data Logs

ParAccel Analy/c Pla8orm

On Demand Integra/on

Enterprise Data Warehouse

Hadoop

Big Data Apps

Embedded Analy/cs


U/lize the Most Dynamic Analy/c Interac/on u  Most extensive interac1ve connec1vity to other plaHorms and data


Machine Data

Opera/onal Data

3rd Party Info

Provider

Streaming Data Logs


On Demand Integra/on Services


Hadoop

Big Data Apps

Embedded Analy/cs

ParAccel Teradata ODI

module

ParAccel Hadoop ODI module

ParAccel ODBC ODI module

U/lize the Most Dynamic Analy/c Interac/on u  Most versa1le integra1on service layer for an analy1c plaHorm 1.  Share both data and processes in both direc1ons 2.  Transform incoming data for analy1c performance 3.  Interact with many programming languages (Java, Python, more) 4.  Persist or stream data through analy1c processing 5.  Rapidly build new On Demand Integra1on modules


Machine Data

Opera/onal Data

3rd Party Info

Provider

Streaming Data Logs


On Demand Integra/on Services


Hadoop

Big Data Apps

Embedded Analy/cs

Deliver Analy/c Services for En/re Ecosystems

Machine Data

Opera/onal Data

3rd Party Info

Provider

Streaming Data Logs



Hadoop

Copyright 2012 ParAccel, Inc. 15

Data Data

Big Data App

Business Process

Embedded Analy/cs

Business Process

Embedded Analy/cs

Business Process

Embedded Analy/cs

Business Process

Embedded Analy/cs

Big Data App

Big Data App Big Data

App

Business Process

Embedded Analy/cs

Business Process

Embedded Analy/cs

Business Process

Embedded Analy/cs

Business Process

Embedded Analy/cs

Big Data App

Big Data App

Big Data App

Big Data App

ParAccel Analy/c Pla8orm -‐  Built for High Performance, Interac/ve Analy/cs

Integrated Analy/cs

Basic Analy1cs

Advanced Analy1cs

On Demand Integra/on

Database

Teradata

Hadoop

Streaming Data

Applica1ons

Parallel Processing

Data Scale

Analy1c Scale

User Scale

Interac1ve Scale


Analy/c Engine

Columnar

Compression

Compiled

SQL Op1miza1on

Plan Op1miza1on

Execu1on Op1miza1on

Comms Op1miza1on

I/O Op1miza1on

In-‐Memory Op/on Available


Run the Highest Performing Analy/c Pla8orm

In-‐Memory Op1on: Lock all data and processes to run in-‐memory

I/O Op1miza1on Intelligent Prefetch, Intelligent Caching of Data In-‐Memory

Communica1on Op1miza1on Packet delivery op1mized for analy1cs, low overhead, plus Virtual Hotwire

Parallel Processing Each node processes, pipelines, and leverages both columnar & compression

Workload Management Establish query classes for long, short, and interac1ve queries

Compiled Queries Queries compiled to run within the database on each individual node

In-‐Database Analy1cs Store and run SQL, aggregate, and analy1c func1ons in the database applica1on

Execu1on Op1miza1on Final op1miza1on based on resources available

Planning Op1miza1on Choose the best from billions of compe1ng plans based on cos1ng model

SQL Op1miza1on Extreme SQL Support with breakdown into 2000 segments, MPP and data-‐aware

Parallel Loading 1TB per node, per hour, up to 160 nodes, without complex data prepara1on

Total Customer Value -‐ Time to Value

Total = 41 hours

Total = 1 minute

Model Build Test Tune Query Load 15 seconds 45 seconds

ParAccel

Oracle Report Building

2 hours 2 hours 3 hours 6 hours 8 hours

Model

20 hours

Load Build Test Tune Query

X X X X


Total Customer Value -‐ Time to Value

Total = 85 hours

Total = 1 minute, 15 seconds

Model Build Test Tune Query Load 30 seconds 45 seconds

ParAccel

Oracle Shrink Processing

46 hours 2 hours 3 hours 6 hours 8 hours

Model

20 hours

Load Build Test Tune Query

X X X X


Deliver Unconstrained Analy/cs

ParAccel Analytic Platform

Unconstrained Analytics Load and Go

Run Ad Hoc Queries

Query Any Time

Query Any Data

Query All Data

Run Any Analytics

Execute Sophisticated Analytics

Return Results Quickly

Iterate Quickly Through Discovery

Share Workloads With Any Platform

Support All Analysts

Run Many Applications

Create Analytic Services


Envisioning Unconstrained Analy/cs

What are the immediate, pending, and “no constraints” opportuni1es for analy/cs?

Immediate Needs

Weekly Market Basket Analysis

Pending Needs

Daily Market Basket Analysis

No Constraints

On Demand Market Basket Analysis Demand signaling



What are the immediate, pending, and “no constraints” opportuni1es for data expansion?

Immediate Needs

Point of Sale + Loyalty + Credit + Pyschographic 2 Years Data

Pending Needs

Partner Data 6 Years Data Archived, Accessible

No Constraints

Social Media Data



What are the immediate, pending, and “no constraints” opportuni1es for analyst communi/es?

Immediate Needs

Business Analysts Pending Needs

Store Managers No Constraints

Suppliers


Increasing Analyst Produc/vity & Innova/on

With ParAccel Before ParAccel

Productivity


Ques1ons and Answers



The Briefing Room

Analyst: Robin Bloor

Perceptions & Questions

The Bloor Group

The Bloor Group

A Schism in BI

BI IS FRAGMENTING BETWEEN TRADITIONAL BI AND ANALYTICS

Hindsight & Oversight Insight & Foresight

Relatively easy to accommodate

technically

Modeling, interactive &

conversational, highly variable

The Bloor Group

Big Data is New Data (Mostly)

MOST OF THE VALUE IS IN

Machine generated data (logs)

Web data

Social media data

Public data services

Supply chain data

Real-time data flows

The Bloor Group

The Data Analytics Issue

The Bloor Group

Conversational Analytics

The Bloor Group

Boiling It Down

It is all about TIME TO INSIGHT – as long as that is followed by action

The data analyst needs to be able to MARSHAL the data

The Bloor Group

!   In my view we have reached a situation where there will be multiple “data engines.” Is that ParAccel’s view?

!   Data analytics is usually 50% data prep (merging, cleansing, joining, transformation, etc.). How does ParAccel accommodate that?

!   There are many analytics approaches and algorithms. What is the breadth of ParAccel’s capability?

!   How does it accommodate algorithmic packages? The R Language?

The Bloor Group

!   In your view, is the “age of the data warehouse” over?

!   What is ParAccel’s attitude to the cloud, or more specifically where would ParAccel recommend cloud deployment?

!   Which sectors/businesses are currently in ParAccel’s “sweet spot”?

!   Which companies/products do you regard as competitors/partners?


The Briefing Room


The Briefing Room

Upcoming Topics

This month: Analytics March: Operational Intelligence

April: Intelligence

May: Integration www.insideanalysis.com


The Briefing Room

Thank You for Your

Attention

Certain images and/or photos in this presentation are the copyrighted property of 123RF Limited, their Contributors or Licensed Partners and are being used with permission under license. These images and/or photos may not be copied or downloaded without permission from 123RF Limited. Certain images fall under a Creative Commons license: Some rights reserved by spike55151

two keys to analytic success: cooperation, collaboration

Technology