A visual, live approach to requirements gathering and business analytic development

Mark Marinelli, VP of Product Management

Rapid Analytics

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Agenda

Why Do Traditional Analytics Projects Fail?

What Is Rapid Analytics?

Demonstration

Rapid Analytics Opportunities In The Business

Conclusion

Q&A

2

We give enterprises a new, agile way to analyze, optimize and control their data and processes. - 15+ years in operation

- Thousands of users at 80+ customers

- Billions of dollars in customer value created

- Major offices in USA, UK, Australia

- 120+ employees

Lavastorm’s software makes business analysts heroes by giving them the power of a programmer to:

• Rapidly unify disparate data

• Easily construct complex analytics

• Effectively deliver actionable insights and results

CUSTOMERS (partial list) PARTNERS AWARDS

Lavastorm Analytics at a Glance

The Problem …

4

70-80% of

Corporate BI

Projects Fail

The Main Cause of Failure – An Understanding of the Real Requirements

5

Requirements Application

Sources of Failure

Poor communication between IT and the business

Failure to ask the right questions

Failure to think about the real needs of the business

Traditional Approach and Technology for BI Thrives Where Requirements Are Slow to Change

Providing

• Reports and

dashboards with

answers to pre-

determined questions

• Analysis of highly

modeled and

cleansed data

• Very limited, pre-

determined drill paths

or very complex

query tools for

technologists

• IT development and

governance

Traditional BI

Uses

Relational DBs

Cubes

Requirements

Design

Implementation

Verification

Maintenance

Best applied where:

• Stability Reigns

Data sources & requirements

change little

• Data is well known, well

controlled

• Technologists answer most,

if not all, the questions

• IT owns all of the source

data

and

But the BI/Analytic Needs of Businesses Have Changed

7

Business Compete on Analytics Customer Expectations

Speed, Specialization

Big Data

Volume, Variety, Velocity

More Complexity

More data, decision makers, change

(ex: N-tier Supply Chains, Fractured Value Chains)

Speed, Accuracy, Visibility

Rapid Analytics Is A New Approach Requiring Different Technologies

Enabled By New Technologies A New Methodology

Emphasis on rapid prototypes, not

traditional specifications

Emphasis on responsiveness and

reactions, not fortune telling or time-

consuming over-engineering

Requires new technology that

enables agile methodology –

choices include self-service BI, data

discovery, mashup options

Data-driven, not schema-driven,

models and analytics

Ability to handle complex, disparate,

dissimilar data structures

Easier UI for end user self-service

Emphasis on direct business end

user interactions rather than using

documentation or working through IT

liaisons

8

9

ETL

BI 5GL

Lavastorm Analytics Engine Overview

Agile Extract, Transform, & Load • Merge any data (e.g. RDBMS, Excel, ERP / CRM,

XML, binary, etc.) – no code required • Big Data ready • Profile, inspect, cleanse, and transform sources

5th Generation Language • Process modeling • Not traditional programming • Rapid visual modeling using pre-built “nodes” • Reusable, sharable components / models

Business Intelligence/Analytics • Self-service control for discovery/ad hoc analysis • No IT involvement • Data visualizations • Automated continuous monitoring/auditing

Rapid

Analytics

Driven By a

Unique

Combination of

Capabilities

Demonstration

10

Problem Description

Telecommunications operator

Goal: Every customer is billed for their services – Analysis necessary to determine where unbilled customers exist, and

optimally why their records are not accurate

Challenges: – Diverse data - multiple acquisitions have produced a mix of multiple billing

systems and a heterogeneous network

– None of the relevant data sources are warehoused, but extracts are produced for other purposes

– No visibility into the problem, so no business case to consolidate data sources into the EDW

– Small team will research and correct the errant account records, so cannot waste effort on false positives

What Did We See In the Demo

Incremental, discovery-based analysis – Real-time, collaborative requirements->implementation->validation

process using intuitive visual tools

Accurate answers in seconds – Business rules are tested with live data, with validations and improvements

applied in real time

– Rapid, low-cost application of hypotheses encourages the search for the exceptions and edge cases which often account for process infirmities

Rapid data acquisition – Initial data sets obtained from raw sources without the need for

intermediaries, structured schema, or warehousing

Self-sufficient data federation and analysis – Ability to manipulate and prepare data sets within the tool fosters

independence from traditional data brokers

– Tools for testing data integrity avoid pollution of these satellite data sets

12

The Benefits of An Agile Approach – Examples from the Field

New Data Sources

400 hours invested with no results using traditional means, but 3 days to a working application with Lavastorm

- Communications Service Provider

Greater Responsiveness

“Sometimes I can get the information I need while I’m in the middle of an IM with somebody, or, if they’re in the meeting, I may have the information before the meeting is over…it almost makes people a little shocked that we can get the answer that quickly.”

- Tom Tannehill, Lead Analyst, CenturyLink

More Visibility

Went from ignoring information because no business case to warehouse the data to uncovering tens of millions of dollars of lost revenue

- Consumer packaged goods company

13

Research, Design

Manufacture Procure Market, Sell, Distribute

Support, Deploy

Opportunities for Rapid Analytics Are All Around In Departmental and Corporate Boundaries

Hire, Manage

Finance

Agi

le

Agi

le

Agi

le

Agile

Agi

le

Agile

3rd Parties, Partners, Competitors Customers

Agile Agile

A Rapid Analytics Solution Can Sit Alongside & Complement Your Traditional BI Infrastructure

Process

Data / BI Infrastructure

Cubes DWs Ent. Apps Marts

Dashboards, Reports

• Data discovery • Continuous analytics • Rapid prototyping • Data integration and

management • Visualizations

Individual Data

Controls

Data

Data

Data

What Does It Really Mean?

User experience – Analytic applications, not reports

– All relevant data is joined and in one place

– Real-time updates are possible

– Changes are expected

– Designed for business users, no IT degree required

IT approach – Data foundation build through light mapping, not heavy modeling

– Work with data “as is”, no cleansing required

– Collaborate with the business throughout

All enabled by new technology that is complementary to traditional BI

Rapid Analytics is an entirely different experience for IT and

information consumers

Opportunities for Rapid Analytics are all around and across

the company – where speed matters

Thank You, Next Steps

Contact Me

Mark Marinelli

Lavastorm Analytics

+1 617-345-5422

mmarinelli@lavastorm.com

Follow Us

www.lavastorm.com

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Lavastorm Analytics

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