BI DRIVEN DATA WAREHOUSING - Amazon S3...#TDPARTNERS16 GEORGIA WORLD CONGRESS CENTER BI DRIVEN DATA...

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#TDPARTNERS16 GEORGIA WORLD CONGRESS CENTER BI DRIVEN DATA WAREHOUSING Siva Veera BI Solution / Software Support Manager, Skechers USA Hugo Sheng Sr Director of Partner Engineering, Qlik

Transcript of BI DRIVEN DATA WAREHOUSING - Amazon S3...#TDPARTNERS16 GEORGIA WORLD CONGRESS CENTER BI DRIVEN DATA...

Page 1: BI DRIVEN DATA WAREHOUSING - Amazon S3...#TDPARTNERS16 GEORGIA WORLD CONGRESS CENTER BI DRIVEN DATA WAREHOUSING Siva Veera BI Solution / Software Support Manager, Skechers USA Hugo

#TDPARTNERS16 GEORGIA WORLD CONGRESS CENTER

BI DRIVEN DATA WAREHOUSING

Siva Veera

BI Solution / Software Support Manager, Skechers USA

Hugo ShengSr Director of Partner Engineering, Qlik

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Agenda

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Introduction Why BI Driven Traditional BI BI Driven Approach

Agile Analytics

Dev Ops Demo OperationalDemo

IntelligentEnterprise

QuestionsBI DrivenArchitecture

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Skechers USA

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LIFESTYLE / PERFORMANCE FOOTWEAR BRAND• Footwear reflects a combination of style, comfort,

quality and value that appeals to a broad range of consumers to satisfy their active, casual, dress casual and athletic footwear needs.

• Skechers products are designed and developed primarily by in-house design staff. In addition, we utilize outside design firms on an item-specific basis to supplement our internal design efforts.

• Skechers objectives are to profitably grow operations worldwide while leveraging and recognizable Skechers brand through strong product lines, innovative advertising and diversified distribution channels.

• There are 1312 company owned and branded stores world wide

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Teradata Environment

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BRIDGE THE GAP BETWEEN TECHNOLOGY AND VISION

• The 2800 Teradata Warehouse Appliance is an Advanced Technology in a compact appliance.

• Skechers reduced 30% of its ETL / ELT time by migrating to 2800 Teradata Data Warehouse Appliance. This new appliance replaced existing 2580 series as data warehouse, data mart, disaster recovery system and analytical sandbox for testing and development.

• Like its predecessor, the 2800 has proven to be a trusted, reliable and highly performant platform.

• Our Teradata platform is fundamental to our ability to serve up Business Intelligence and analytics across Skechers global enterprise.

• In a nutshell we have found Teradata to have- Tremendous ease of use - High Performance- Rock solid reliability - Happy IT / Business users

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Qlik Environment

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INSIGHTS AT THE SPEED OF THOUGHT

See the whole story that lives within your dataInnovative associative model enables users to probe all the possible associations that exist in their data, across all data sources, to answer not just “What happened?”, but “Why?”, and “What is likely to happen?”

An open platform for all your visual analytics needsMore than a tool, Qlik’s open platform approach enables centrally deployed guided analytics, self-service data visualization, embedded and custom built analytics, collaboration, and reporting

Agility for the business user, with trust and scale for ITSupports the business and IT; data sourcing and preparation, visualization and analytics, collaboration, and reporting — all within a governed framework

Why Qlik’s approach is uniqueA visual analytics platform

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Why BI Driven

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BUSINESS INTELLIGENCE ACROSS ALL DATA LAYERS ACROSS ALL STAGES OF DATA

DATA SOURCES

STAGED DATA LAYER

FOUNDATION DATA LAYER

ACCESS & PERFORMANCE LAYER

REST SERVICES

External

Internal

Operation

Un-Structured

Temporary Staged

environment

!Rejected

NeutralModels

Embedded Datamarts

Functional Datamarts

Aggregates

Sand Boxes

• Data can be accessed by BI tools across layers allowing broader analysis and association among entities

• Access data from Access & Performance layer along with Staged to give real time data

• Merging REST service calls along with internal data will help in operational decisions

• Additional Sandpit area allows more opportunities for further analysis and add additional functional models

• Slicing and dicing data at Staged data layer allows to create a neutral incremental model

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Finding Value

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1. Focus on the biggest and highest value opportunities.

2. For every opportunity, start with a question without data in mind.

3. Work on the actions and embed insights to deliver the value

4. Work on the incremental, by keeping existing capabilities and begin to add new ones

5. Plan for the future and derive another question to continue the educative process

VALUE

OPPORTUNITY

INSIGHTSINCREMENTALS

FUTURE QUESTION

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How Traditional BI Works

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Analytics Advancement with Maturity

Gro

wth

Ad

vant

age

Reports

Cleane

d

Raw

1. REPORTINGWhat Happened ?

2. ANALYZINGWhy it Happened ?

Increase in Ad-hoc queries & OLAP

3. PREDICTWhat will happen ?

Analytics modeling grows with requirements

Sense & Respond

Predict and Act

4. OPERATIONALIZEWhat is happening ?

Continuous updates and time sensitive information becomes important

5. INNOVATEWhat should happen ?

Optimization occurs

DISCOVERY

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How an Agile BI Environment Works

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KPI ANALYTICSAGGREGATESETL/ELTPROTOTYPE

Story Board

Sample Data

Analyze using Qlik

Re-Organize

Schedule Jobs

Validate

BTEQ / VIEWS

Build Aggregates

Dashboards

Reports

Self Service Data

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BI Driven Approach

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Driven by Instinct and Intuitions Fact driven

Corrective Directive and Focused

Years, Months and Weeks Hours, Minutes and Seconds

Decision Support Action Support

Efficient Optimized

TRADITIONAL APPROACH AGILE BI DRIVEN APPROACH

Enterprise Data Warehouse Functional Business Models

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BI Driven Architecture

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• Expand Enterprise Data warehouse as a Business Data Lake

• BI Across all stages using Qlik in memory associative engine for further prototyping to build functional models.

• Eliminate a requirement for creating a data model up-front. Allow the model to grow with requirements.

• The Functional models provides a loosely coupled architecture that enables flexibility of analysis.

• Leading organizations are utilizing advanced natural language generation (Advanced NLG) to transform their data into narratives.

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BI Architecture

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DEV OPS

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• Analyze error tables with respective codes in Teradata UV and ET tables

• Identify the source of the error and continue to monitor

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OPERATIONS DEMO

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SALES PROJECTION DAILY TREND ANALYSIS STALLED ORDERS

• Fleet App was designed for operations team to analyze regular inventory and dedicated inventory.

• Mashing up data with external source as REST service calls without staging the data helps in real time visualization of how shoes are anchored/docked or moving in the ocean.

• Calculate ETA based on Latitude, Longitude and average speed information obtained from a third party company and then derived calculated ETA dates using Teradata geospatial functions in real time then compared to Actual ETA to check variations.

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JOURNEY TO INTELLIGENT ENTERPRISE

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1. Profitable Growth2. Proactive3.Optimized & Efficient

DATA AWARE

CONNECTS & LINKED

ACCURATE & PRECISE

ASK QUESTIONS

EMPOWERING

FUTURE VISIONS

Instead of reacting prepare for future functional models

Connects internal and eternal functions across geographies

Deliver information in ways that are useful and precise for the situation handled.

Create more opportunities by raising questions from the solutions found

With DAAS enable and extend insights from the user community with the authority to make higher value decisions and act on them

Gathers structured and unstructured data at higher speed

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Thank You

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