Take Action: The New Reality of Data-Driven Business

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The Briefing Room

Take Action: The New Reality of Data-Driven Business

Twitter Tag: #briefr

The Briefing Room

Welcome

Host: Eric Kavanagh

[email protected] @eric_kavanagh


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


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Topics

2014 Editorial Calendar at www.insideanalysis.com/webcasts/the-briefing-room

This Month: INNOVATIVE TECHNOLOGY

August: BIG DATA ECOSYSTEM

September: INTEGRATION & DATA FLOW


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Executive Summary

The definition of “real-time” is changing: Should we call it customer time?

A stitch in time saves nine… We have reached an inflection point!


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Analyst: Robin Bloor

Robin Bloor is Chief Analyst at The Bloor Group

[email protected] @robinbloor


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WebAction

! WebAction offers real-time data-driven apps and the underlying enterprise platform

!   The platform captures structured and unstructured data from a wide variety of data sources and allows users to correlate and enrich data streams

! WebAction leverages in-memory data processing and is architected to scale up and scale out


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Guest: Sami Akbay

Sami Akbay is a founder of WebAction. Prior to WebAction, he served as the CEO of Altibase, Inc., an in-memory RDBMS company with customers in financial services, utilities, and telecommunications. Sami was Vice President of Marketing and Product Management for GoldenGate Software from 2004 through its acquisition by Oracle. Prior to GoldenGate, he served in senior product marketing and business development roles at Embarcadero and AltoWeb. He spent his earlier career in technical and consulting roles working at Rabobank Nederlands, Hearst New Media, American Stock Exchange, MediaMetrix, OneMain.com (Earthlink), and ALK Associates. He is a graduate of Rutgers University.

The Future of Data Driven Apps July 2014

WebAction® delivers the leading Real-time App Platform

enabling the next generation of Data Driven Apps for the Agile Enterprise

Proactive

WebAction – Streaming Data – Continuous Processing

Reactive

Historical Data – Batch Processing

Load data into cluster

PRIOR to running analytic queries

Write MR jobs - Time delay before data processing

and analysis

Efficient for BATCH oriented

workloads

WebAction collects Big Data from the

sources, converts it into DATA STREAMS

Processes data in

REAL-TIME

Minimizes latency

ALERTS based on

LIVE DATA

Acquire Store Process

Acquire Process in Memory Deliver

BI / Analytics RDBMS EDW

Structured Data

Machine Data

Location Click Stream

Structured Data

Machine Data

Location Click Stream

Data Driven Apps

Batch Reactive

REALTIME BARRIER

Proactive Real-time

Visualize Store

Alerts Integrate

Structured and unstructured data

Distributed, in-memory, as data is created

Correlated, enriched, and filtered real-time big data records

Deliver

Process

Acquire

Acquire Structured and unstructured data

§  Data from transactional sources is acquired via redo or transaction logs

§  Structured and non-Structured data

§  No Production Impact

§  No Application changes

Device Data

Industry Data

Social Feeds

Real-time Transaction Data

System/ IT Data

Common File Format

TYPE EXAMPLE COMPLEXITY

CSV, JSON, XML

Facebook, Twitter

Syslogs, weblogs, Netflow

SmartMeter, Medical Device, RFID

SWIFT, HL7, FIX

Oracle, DB2, SQLServer, MySQL, HP NonStop

SIMPLE

VERY HIGH

SIMPLE TO MEDIUM

MEDIUM

MEDIUM

HIGH

Process Distributed, in-memory, as data is created

§  Enrich live Big Data with historical data sources

§  Process Big Data faster using partitioned streams, caches, and additional nodes

§  Execute SQL-like queries of in-memory Big Data

§  Alert in real-time based on predictive analytic model results

Acquire Structured and unstructured data

Acquire

Process

Structured and unstructured data

Distributed, in-memory, as data is created

Deliver Correlated, enriched, and filtered real-time big data records

§  Continuous Big Data Records §  Real-time Dashboards & Visualizations §  Predictive Alerts §  Business Trends §  Data Patterns §  Outliers & Anomalies

Historical Data Cache

Node

Node

Node

Metadata

High Speed D

ata Acquisition

WActionStore

Distributed WAction Cache

Distributed DIM Processor

Tungsten Visualization Device Data

Big Data Infrastructure

Industry Data

Social Feeds

Transaction Data

Enterprise Applications

Enterprise Data Warehouse

RDBMS

Data Driven Apps

System/ IT Data

§  Integrated end-to-end solution for real-time data acquisition, in-memory analytics, event correlation, and relevant data storage

§  Supports transactional and non-transactional data sources

§  Scalable, High Performance distributed stream processing

§  Supports low-impact, non-intrusive capture from transactional databases

§  Processing in-memory, delivering real-time results via applications that can Incorporate predictive analytics (linear regression, FFT, clustering, etc.) models.

§  Runs on inexpensive commodity hardware, easily allowing horizontal scaling by adding nodes on the same or multiple machines.

§  Declarative configuration, Continuous querying capability

§  Real-time visualizations, monitoring, alerts, and integration


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Perceptions & Questions

Analyst: Robin Bloor

Data-Driven Things?

Robin Bloor, PhD

Everything

EVERYTHING that is ALIVE

is Data-Driven

Big Data Architecture

The Biological Analogy

u  Our human control system works at different speeds: •  Operational control •  Almost instant reflex •  Considered response

u  Organizations will gradually implement similar control systems

u  This suggests a data-flow- based architecture

Nervous System(s)

u  Mentation •  The Brain

u  Fight or Flight •  Sympathetic Nervous

System u  Operational Control

•  Enteric Nervous System •  Parasympathetic Nervous

System

Note that these three systems integrate. It would be bad

news if they didn’t.

The Corporate Biological System

u  Right now this division into two different data flows is already occurring

u  Currently we can distinguish between: •  Real-time/Business time

applications •  Analytical applications

u  We should build specific architectures for this

u  Is there any significant distinction between WebAction’s technology and what was previously called complex event processing?

u  How would you compare WebAction with Apache Storm? Is it directly competitive?

u  How would you compare WebAction with Splunk?

u  What do you see as the sweet spot for this technology? Dashboards? Real-time triggers? Streaming analytics?

u  What is the typical process for developing predictive analytics applications?

u  Please provide some examples of usage/ user application stories.


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Upcoming Topics

www.insideanalysis.com

2014 Editorial Calendar at www.insideanalysis.com/webcasts/the-briefing-room

This Month: INNOVATIVE TECHNOLOGY

August: BIG DATA ECOSYSTEM

September: INTEGRATION & DATA FLOW


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THANK YOU for your

ATTENTION!

Take Action: The New Reality of Data-Driven Business

Technology

Transcript of Take Action: The New Reality of Data-Driven Business