LOGITECH CONFIDENTIAL

Avinash Deshpande

Chief Software Architect

adeshpande2@logitech.com

Powering Machine Learning and Analytics with Logical

Data Lake

WE DESIGN PRODUCTS THAT CONNECT YOU

3TO THE DIGITAL EXPERIENCES YOU LOVE

A UNIQUE COMPANY

Start-upsBig Companies

$2.22 billion in sales in FY17, strong cash, no debt

7,000 employees

30 countries

SIX Swiss Exchange: LOGNNASDAQ: LOGI

3 strong identities

5 big market opportunities

1 big market driver

5 core capabilities

3 key advantages:

A GREAT SMALL COMPANY

GLOBAL NETWORK

350+ customers

2,000+ locations

2 week delivery fromfactory to family in100 countries

Decade-long relationships with key retailers and e-tailers

3 million products shipped per week to 100 countries

Select partners and customers

DIVERSE PORTFOLIO OFPRODUCTS AND BRANDS

VIDEOCOLLABORATION HOME

GAMINGCREATIVITY & PRODUCTIVITY

MUSIC

LOGITECH CONFIDENTIAL

LOGITECH CONFIDENTIAL

HOME SECURITY AND ENTERTAINMENT

CONTROL

We design simple, yet powerful products that help people take

control of their ever-growing connected home.

LOGITECH CONFIDENTIAL

VIDEOCOLLABORATIONLogitech is transforming video conferencing by offering an easy and affordable way to collaborate with crystal-clear audio and razor-sharp video.

LOGITECH CONFIDENTIAL

BRING MUSIC TO LIFEUltimate Ears empowers you to spontaneously transform your world with music.

LOGITECH CONFIDENTIAL

POWER YOUR PASSIONJaybird is an authentic sports brand leading with innovative design that elevates an active life.

LOGITECH CONFIDENTIAL

ADVANCE PLAYLogitech G applies our leadership to one pursuit: advancing the performance and passion for play.

LOGITECH CONFIDENTIAL

PROGAMINGEQUIPMENTASTRO Gaming, creates premium video gaming equipment and lifestyle products for professional gamers, leagues, and gaming prosumers.

LOGITECH CONFIDENTIAL: NOT FOR DISTRIBUTION

ANALYTICS AT SCALE

SUPPORTING OUR GROWING BUSINESS

LOGITECH DATA USE CASES

Structured Semi-Structured Unstructured

Ba

tch

D

ata

Ve

loc

ity

Re

al-

Tim

e

Social Media

Sentiment

Predictive

Analytics

Demand

Forecasting

Price violations

on Retail sites

Data

WarehousingText Mining

Security Video

Analysis

Retail Data

scrapping

Machine

Learning

ioT

Multi site ERP

Marketing Funnel

Sales Channel

Mgmt

Smart Home

Natural Language

Processing (NLP) VR Gaming

Device Events

ANALYTICS AT SCALE - SUMMARY

• Create a decentralised self-service analytics environment for traditional business reporting and

analytics (Descriptive and Diagnostic Analytics). Becomes a purely EXPLICIT experience.

• Allowing for a centralised, cross-functional shared advanced analytics service tasked to deliver Predictive and Prescriptive analytics to the organisation. • A minimal investment, with leveraged return.

• Logitech and Competitors Products Consumer Reviews

▪ Core capabilities to scrape retail websites for consumer reviews

▪ Raw and structured data available for advanced analysis

▪ Petabyte data volumes support and performance

▪ Sentiment analysis for business decision

▪ BGs data analysis for consumer complaints and issues and negative reviews

• Logitech Product Pricing

▪ Core capabilities to scrape retail websites for pricing of Logitech products

▪ Amazon buy button analysis

▪ Amazon.com and marketplace price analysis

▪ Price violation analysis

DATA VOLUME – COMPLEXITY(RETAIL USE CASE)

Logitech connected devices generate events and are streamed as real-

time/micro-batches for analysis and insight.

▪ Need for tactical KPIs

▪ Engineering feedback on issues

▪ Marketing segmentation for cross sell/up sell

DATA VOLUME – COMPLEXITY (IOT USE CASE)

LOGITECH CONFIDENTIAL: NOT FOR DISTRIBUTION

NEW TECHNOLOGY

A VISION

PRICE ANALYSIS

Demo

SELF SERVICE

LOGITECH CONFIDENTIAL

DemoNLP Demo

TEXT ANALYTICS

NATURAL LANGUAGE PROCESSING

YTD Sales by Product

Furniture in the Corporate segment and Chairs sub-category

accumulated $24,304 in YTD sales (3.8% of Superstore's total).

This cell accounted for the greatest proportion of sales in the

Corporate segment (45.1%) and the second highest proportion of

sales in the Chairs sub-category (31.1%).

Q3 recorded the largest proportion of sales (30%), though the

largest sales week was in the second quarter (May 4, 2014;

$2,297). As a result of a moderate profit ratio (13%) and high

order profitability (91%) overall, total profit from Corporate Chair

orders was $3,263. The Central Region contributed the most to

profit ($1,703), while the East Region had the best profit ratio

(23%).

This year's Corporate Chair orders shipped on time or early 79%

of the time. This could be associated with solid performance in

Standard Class Shipping, where 96% of orders shipped on time

or early. Another probable reason was the Central Region, where

83% of orders shipped on time or early.

SAAS INTEGRATION PLATFORM

LOGITECH CONFIDENTIAL: NOT FOR DISTRIBUTION

REAL-TIME ON DEMAND delivery to your PHONE and DESKTOP and DASHBOARD

Executive Summaries

Customer by Product

Product by Customer

Demand / Supply updates

Market Analytics / Market Share

Marketing Reports

Competitive Analysis

Sentiment

...

NLP is a scalable self-service environment,

meaning we can open it to business users

(self-service) and allow them to improve and

drive business impact and adoption. It is

language agnostic, meaning we can publish

reports in the language they are written.

LOGITECH CONFIDENTIAL

DemoSlackBot

HOW DID WE GET THERE?

REFERENCE ARCHITECTURE

Metadata Management, Data Governance, Data Security

Cost and Usage Pattern

Sensor Data

Machine Data Logs

Social Data

Clickstream Data

Internet Data

Image and Video

Cloud Applications

Enterprise

Applications

Data Sources Data Insights

Self-Service /

Data Discovery

Reporting

Predictive Analytics

Statistical Analytics

Sentimental Analytics

Text Analytics

Data Mining

Data VirtualizationData Collection

Real-Time Data Access (On-Demand / Streaming)

C

D

C

E

T

L

EDW

ODS

Cloud

DW

NoSQL

Data Warehouse

File Storage (S3)

Batch DWSpark

SQL

NoSQLSearch Search

Big Data

InMemory

Analytical

Appliances

Real-Time

Decision Support

Alerts

Scorecards/

Dashboards

SOLUTION ARCHITECTURE

AAmazn Web Services

AWS GlacierAWS S3 AWS Redshift

Pentaho DI

Pentaho Operations Mart

Cloudwatch SNSIAM Cloudtrail EMR SPARKPython /

R

AWS RDS

Denodo Data Virtualization

Tableau Pentaho BA Data Interfaces Web ServicesOBIEE CUBES

SnowflakeText

Analytics

Records

JSON

Read raw

JSONWrite to

HDFS

as Parquet

Cleaned

and/or

aggregated data

Data Virtualization /

Blended DataBusiness Reporting

high computation needed analysis

AWS Glue: fully managed ETL service that can categorize your data, clean it, enrich it, and move it reliably between various data stores.

Snowflake: Cloud datawarehouse

S3: Data Storage

Denodo: Data Virtualization provides business agility by integrating disparate data from any enterprise source, Big Data and Cloud.

Tableau: Data Visualization

Zeppelin: Web-based notebook that enables data-driven, interactive data analytics and collaborative documents with SQL, Scala, pyspark and more

Apache Parquet: a columnar storage format available to any project in the Hadoop ecosystem

DATA VIRTUALIZATION IN IOT ECOSYSTEM

Other RDBMS(apps, CRM, SAP)

Other Sources(SaaS, SFDC, etc.)

Ingestion Streaminganalytics

Big Data Storage

Batch analytics,Machine learning

Streaming data

Traditional batch processing (ETL to EDW)

Semantic Model

Secure+

Combine+

Enrich

Meta Base

INTEGRATION WITH IOT - STREAMING

Ingestion buffers Streaming Analytics Storage

Read temp window buffers

SQL basedenrichment

Secure +

Combine +

Enrich

JOURNEY TO CLOUD

Cloud empowers IT organizations to redefine the way Data services are produced

and delivered

Scalable • Infrastructure scaled up - down on the fly (Elastic)

• Focus on simplicity, security, robustness, and scalability

Efficient • Infrastructure costs are pay as use

Reliable• AWS managed services

Managed & Governed

• Transparency on usage patterns

• Breadth of services offered, pricing, performance and flexibility

IMPACT OF DATA VIRTUALIZATION PLATFORMS

By 2018, organizations with data virtualization

capabilities will spend 40% less on building and

managing data integration processes for

connecting distributed data assets.”

-Gartner

NEED FOR DATA VIRTUALIZATION

Abstract access to disparate data sources

A single semantic repository

Optimized data availability in real-time to consumers

Centralized, governed and secured data layer

MANAGING BIG DATA WITH DATA LAKES

➢ Organizations are exploring data lakes as consolidated repositories of massive volumes of

raw, detailed data of various types and formats to overcome Big Data challenges.

➢ But creating a physical data lake presents its own hurdles, one of which is the need to store

the data twice which can lead to governance challenges with regard to data access and

quality.

➢ Data Virtualization technologies can improve an organization’s ability to govern and

extract more value from its data lakes by extending them as logical data lakes.

- Ventana Research

BIG DATA FABRIC

Denodo Data Virtualization

•Logical model can be predefined for the data

•Eliminates load processes and the need to update the data

•Uses the security and governance system already in place

•Collects and maintains statistics and determines optimal query execution

•Avails Cache mechanism and pushdown for optimal performance

•Array of connection options from structured to unstructured data

•Business Layer, enabling data Consistency through single object, multiple consumers

•Rapid prototyping

•Data Audits

•Sandbox for data science

VIRTUALIZATION BENEFITS

•Catalog exploration

o Graphical representation of data model

o Data lineage

o Integrated catalog search

•Data Discovery

o User friendly query wizards with drill down capabilities

o Export to CSV, Excel and Tableau Data Extracts

•Secure

o Leverages Denodo’s security model and access control

o Available vis SSL/TLS

GOVERNANCE - DENODO INFORMATION SELF

SERVICE

CLOUD AND DV BENEFITS

• Proactive – IT has embraced cloud as a model for achieving

innovation through increased efficiency, reliability and agility

• Reusability and template development

• Rapid innovation within governance structure, balanced

costs, risks and service levels

• Greater efficiency and reliability, enabling broader audience

to consume IT services via self-service

LESSONS LEARNT

•Reduced Spend

•Live migration

•Flexible and cost effective

•Better business continuity

•Speed to deliver

•Easier to manage

•More efficient IT operations

•low hardware costs

•No or reduced Software costs

Cons

•Possible learning curve

•Accountability

•Getting all vendors to gel well

Pros

BENEFITS

• Adds context to device data

▪ Enrichment and augments with other sources (internal or external)

▪ No replication: enables Virtual Data Lake

▪ Simplifies publication of useful results

▪ End-user oriented semantic model

▪ Reports and dashboards in SQL

▪ Data as a service (REST, OData)

▪ Improves governance

▪ Security (AD integration, data restrictions, masking, etc.)

▪ End-to-end lineage

▪ Abstraction of source technologies

DATA VIRTUALIZATION – NIRVANA

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