Becoming (Big) Data Driven

Geert Van Landeghem

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Big Data Consultant@DataCrunchers

geert@datacrunchers.eu

From Vision to Implementation

References

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The Ubiquity of Data Opportunities

Continuous investments in business infrastructure

Virtually every aspect of business can be measured

More and more External data is available

More interest into getting information out of data

Data mining versus data science

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From Business Problems to Data Mining

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Data mining tasks

Classification

Regression

Clustering

Profiling

Similarity matching

Co-occurence grouping

Data reduction

Link prediction

Casual modeling

Data Science Context

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How DDD affects performance

The more data driven a firm is, the more productive it is!

One standard deviation higher on the DDD scale is associated with a

4%–6% increase in productivity.

DDD also is correlated with higher return on assets, return on equity, asset

utilization, and market value, and the relationship seems to be causal

Source: Study by Economist Erik Brynjolfsson and his colleagues from MIT (2011)

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Data Driven marketeers outperform their competition

Source: The State of Marketing 2013, IBM’s Global Survey of Marketeers

Many leaders are data-driven

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What does it mean to be data-driven?

The culture and capabilities that

operationalize capturing, processing, and

utilizing data to make timely decisions

that improve products, customer

experiences, operational efficiency and

competiveness.

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Data driven hurdles

Disparate Data Sets

Data owned by different silos within the org

Lack of funding

Lack of time/resources

Legacy operating rhythm

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Embarking on your data driven journey

Transformation will not happen overnight

Support of C-Level (top-down)

Requires cross-functional collaboration

Combination of people, process, tools

Cultural champion is needed

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How does big data fit in?

Big data refers to data that is too big to fit

on a single server, too unstructured to fit

into a row-and-column database,

or too continuously flowing

to fit into a static data warehouse

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Big Data Technical Drivers

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Big Data Business Drivers

Do More (Analytics) with Less (Costs)

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Big Data Driven Roadmap

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Source: Bill Schmerzo (EMC)

How to build the 360° view?

Two-way data integrations across

multi-channels

Data is always updated and

accessible for use

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The Enterprise Data Hub

Enterprise Data Hub Definition

Contains all enterprise data

Internal & External

Processes all data in „near real-time” to generate views

Historic & Flowing

Views

Answers to business questions

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A Common Start Situation

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Our Vision #1

Focus on Data not on Derived Data

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Our Vision #2

Data is immutable

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Our Vision #3

Query = function (all data)

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Conceptually

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Lambda architecture

View generation

- Use machine learning

Recommendations

Clustering

Classification

Regression

R

…

- SQL Like (Hive)

- Data Flow Programming (Pig)

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References

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