instant gratification: taking the fast track to visual analysis

Grab some coffee and enjoy the pre-show banter before the top of the hour!

The Briefing Room

Instant Gratification: Taking the Fast Track to Visual Analysis

Twitter Tag: #briefr

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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


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Topics

This month: DATA DISCOVERY & VISUALIZATION

December: INNOVATORS

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


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Data Discovery & Visualization


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Analyst: Robin Bloor

Robin Bloor is Chief Analyst at The Bloor Group

[email protected]


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Acunu

! Acunu offers a Cassandra-based real-time operational intelligence and analytics platform

!   Its platform allows Cassandra users to build and extend business applications without being a database expert

! Acunu Analytics provides the ability to leverage customizable and re-usable analytic apps and widgets on top of its analytics layer, and it automatically recommends the most appropriate visualization


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Guest: Tim Moreton

Tim is an expert in distributed file systems. He was previously a senior member of the technical team at Tideway (now BMC), where he led the creation of solutions for managing data centers at Fortune 500 clients. Previously he was CEO of a consultancy delivering data solutions for the aviation sector. He holds a Ph.D. in Computer Science from Cambridge University.

Tim Moreton CTO @timmoreton

Instant Gratification: Taking the Fast Track to Visual Analytics

Big Data: Haystack or FastTrack

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Discovery Analytics

Unstructured��Warehouses

Data ��Mining

Machine Learning

Operational Intelligence

Dashboards Real-time Decisions

Alerting

Complex, long-running Total lack of structure

Low latency, fresh data Some structure to exploit

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Metrics dashboards�� and business intelligence

Trending and alerting OPERATIONAL ��INTELLIGENCE

Data-driven features

Embedded dashboards

RICHER��APPLICATIONS

Location Data

Clickstream

Application logs

Infrastructure

Fast Datasets

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Analytics turns events and SQL-like queries into C* operations

Events

Cassandra stores raw events and intermediate results

Acunu Dashboards: embeddable, in-browser visualizations

Alerts

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Acunu Analytics: BI for Fast Datasets

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Ø  Scalable. No single point of {failure, bottleneck}

Ø  Fast. Especially for writes

Ø  Available. Effortless Multi-DC support

Ø  Dependable. Widespread mission-critical use

Ø  Counters. Building block of analytics!

WE

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count by day count by hour of day

top keywords by browser

1 Define aggregate cubes CREATE CUBE APPROX TOP(keyword) WHERE browser, time GROUP BY time !

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2 New events update cubes


top keywords by browser raw events

1 Define aggregate cubes CREATE CUBE APPROX TOP(keyword) WHERE browser, time GROUP BY time !

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3 Rich instant queries over cubes SELECT TOP(keyword) FROM table WHERE browser = ‘chrome’ AND time BETWEEN.. !GROUP BY d1, d2, ... !JOIN ... HAVING.. ORDER BY .. !

+

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1 Define aggregate cubes CREATE CUBE APPROX TOP(keyword) WHERE browser, time GROUP BY time !2 New events update cubes




+

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4 Drilldown to raw events




+

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5 Populate new cubes from historic data

2020

Ø  Platform for user-generated radio content 300,000+ active uploaders

Ø  Millions of monthly listeners

Ø  Server and site metrics Ø  User engagement funnels Ø  Leader boards Ø  Analytics for uploaders

CASSANDRA AND ACUNU DELIVER:

Ø  World’s top-rated taxi app Ø  Serving 15 cities globally Ø  500,000 registered users Ø  Clusters in 3 AWS regions

CASSANDRA AND ACUNU DELIVER:

Ø  Instant driver, user metrics Ø  Real-time A/B testing Ø  In-app location analytics

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Install 1 Create tables 2 Define

cubes 3 Turn on data feed 4 5 Refine

cubes 6

Dev Dev Dev Dev Business Dev

5

With Acunu Analytics 4.3

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Six steps to enlightenment

Build widgets


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Enlightenment for mere mortals

Install 1 2 Turn on data feed 4 3

Dev Dev Business Business Business

3 2 Upload events

Build widgets 5 Refine

widgets


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Install 1 2 Turn on data feed 4 3 5


3 2 5 Upload events

Build widgets

Refine widgets

Automatically infer tables and schema from sample events


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3 2 5 Upload events

Build widgets

Refine widgets

Drag-and-drop Explore view infers the cubes needed to build the widget you want


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3 2 5 Upload events

Build widgets

Refine widgets

Widgets can be refined and repopulated with historic data automatically


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3 2 5 Upload events

Build widgets

Refine widgets

Out-of-the-box HTTP, Flume, Kafka and MQ integrations, ��plus new API to build your own

Tim Moreton CTO @timmoreton @acunu

Thanks!


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Perceptions & Questions

Analyst: Robin Bloor

A Maturing Analogy

Exaggerated comparisons between computer systems and the biological nervous system have been made for decades

Maybe such comparisons are no longer so exaggerated

The Human System

u  The body is controlled via the autonomic nervous system: •  Enteric (gastrointestinal

system) •  Sympathetic (fight or flight,

homeostasis) •  Parasympathetic (rest-and

digest, feed-and-breed) u  This constitutes the fast

human response system – the operational system

The Human Brain

u  The human brain complements the autonomic nervous system

u  In general, it is much slower, even when working at its highest speed (about 0.1 secs response)

It interprets sensory

impressions

It reasons and learns

It thinks associatively

Enterprise Information Processing

Pursuing the analogy, there is a slow and a fast enterprise control system/nervous system:

u  SLOW: This equates to normal BI and embraces everything from data analysis/data science to BI reporting

u  FAST: This equates to Operational Intelligence – those BI systems which provide information to enable immediate response by people or software

Real Time is What?

We define a real-time latency to be one where there is operational urgency. Operational Intelligence can be thought of as real-time.

u  Data analysis may yield knowledge that can be implemented as OI

u  OI should be served to software as data

u  OI should be served to users in context and in its most easily digested form: alerts, visualization

u  It demands fast infrastructure

THE CONTEXT DETERMINES THE INFORMATION SERVICE, AND ITS CHARACTER AND REQUIRED SPEED

Going Forward

Ultimately, SOFTWARE

ARCHITECTURE will be determined by these differing

latencies.

u  What is the role of Cassandra?

u  Typically what latencies does Acunu need to satisfy?

u  There are many varieties of data visualization; which techniques and UI features does Acunu regard as being most important and why?

u  OI systems can take considerable time to build. What does a normal Acunu implementation involve and how long does it take?

u  Which industry sectors do you see as early adopters of BI?

u  What is Acunu’s Hadoop story? Is Hadoop relevant to Acunu?

u  What is your view of the OI market? Who do you see as competitive and who do you see as complementary?


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Upcoming Topics

www.insideanalysis.com

November: DATA DISCOVERY & VISUALIZATION

December: INNOVATORS

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


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Thank You for Your

Attention

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