Review workplace sustainability policy implementation

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Data Analytics Lifecycle

1 M

odule 2: Data Analytics Lifecycle

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Data Analytics Lifecycle

U pon com

pletion of this lesson, you should be able to: •

Apply the Data Analytics Lifecycle to a case study scenario •

Fram e a business problem

as an analytics problem

• Identify the four m

ain deliverables in an analytics project

M odule 2: Data Analytics Lifecycle

2

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How to Approach Your Analytics Problem

s

• How

do you currently approach your analytics problem

s?

• Do you follow

a m ethodology or

som e kind of fram

ew ork?

• How

do you plan for an analytic project?

3 M

odule 2: Data Analytics Lifecycle

Your Thoughts?

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• Focus your tim

e

• Ensure rigor and com

pleteness

• Enable better transition to m

em bers of the cross-functional

analytic team s

Repeatable Scale to additional analysts Support validity of findings

4

“A journey of a thousand m iles begins w

ith a single step“ (Lao Tzu)

M odule 2: Data Analytics Lifecycle

Value of U sing the Data Analytics Lifecycle

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1. W

ell-defined processes can help guide any analytic project

2. Focus of Data Analytics Lifecycle is on Data Science projects, not business intelligence

3. Data Science projects tend to require a m

ore consultative approach, and differ in a few

w ays

M ore due diligence in Discovery phase

M ore projects w

hich lack shape or structure Less predictable data

N eed For a Process to Guide Data Science Projects

5 M

odule 2: Data Analytics Lifecycle

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Key Roles for a Successful Analytic Project

M odule 2: Data Analytics Lifecycle

6

Role Description

Business U ser

Som eone w

ho benefits from the end results

and can consult and advise project team on

value of end results and how these w

ill be operationalized

Project Sponsor Person responsible for the genesis of the project, providing the im

petus for the project and core business problem

, generally provides the funding and w

ill gauge the degree of value from

the final outputs of the w orking team

Project M anager

Ensure key m ilestonesand objectives are m

et on tim e and at expected quality.

BusinessIntelligence Analyst

Businessdom ain expertise w

ith deep understanding of the data,KPIs, key m etrics and

business intelligence from a reporting perspective

Data Engineer Deep technical skills to assist w

ith tuning SQ L queries for data m

anagem ent, extraction and

support data ingest to analytic sandbox

Database Adm

inistrator (DBA) Database Adm

inistratorw ho provisions and configures database environm

ent to support the analytical needs of the w

orking team

Data Scientist Provide subject m

atter expertise for analytical techniques, data m

odeling, applying valid

analytical techniques to given business problem s and ensuring overall analytical objectives

are m et

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C Corporation. All Rights Reserved.

Data Analytics Lifecycle

M odule 2: Data Analytics Lifecycle

7

D iscovery

O perationalize

M odel

P lanning

D ata P

rep

M odel

B uilding

C om

m unicate

R esults

Do I have enough inform