BI landscapes are becoming increasingly complex with the surge in adoption of cloud technologies. Your BI group may have one foot in legacy systems and the other in more modern cloud-based systems, and this alone makes managing and understanding your data virtually impossible. From needing to understand the impact of a change in a source system from the ETL through to reporting, to finding the source of a reporting error that an end-user questioned you on, to quickly responding to auditors’ demands – these recurring daily BI tasks and more turn into weeks-long projects. Join us for our upcoming webinar where you’ll learn: • How to enable your BI group to fix problems sooner for quicker access to accurate data • The advantages of moving from manual to automated data lineage • Use cases for BI and analytics groups in a variety of industries, including finance and insurance

2. www.octopai.com
Agenda:
1. Introductions ( 5 min)
2. Deep Dive into How Automating Data Lineage Improves BI Performance
(Cloud Migration Use Case – 30 min)
3. Quick Review of Automated Data Lineage in Octopai ( 5 min)
4. Questions and Answers ( 20 min)

3. www.octopai.com
Introductions

4. Amnon Drori Biography
pg
© 2021 Data Millennium www.datamillennium.com
Amnon Drori
Amnon is the CEO and Co-Founder of Octopai, a leader in metadata
management automation for BI. With over 20 years of leadership
experience in technology companies, before co-founding Octopai Amnon led
sales efforts at companies like Panaya, Zend Technologies, ModusNovo and
Alvarion, and also served as the Chief Revenue Officer at CoolaData, a big
data behavioral analytics platform. Amnon studied Management and
Computer Science at the Open University of Tel Aviv.
https://www.linkedin.com/in/amnon-drori-b0286b1/?trk=hp-identity-name

5. Malcolm Chisholm Biography
pg
© 2021 Data Millennium www.datamillennium.com
Malcolm Chisholm has 30+ years of experience focused on data and its usage, and is a recognized
international expert in Data Governance and Data Management. He has written three books:
• Managing Reference Data in Enterprise Databases
• How to Build a Business Rules Engine
• Definitions in Information Management
Additionally, Malcolm speaks frequently at conferences, and writes in the trade publications.
As a consultant, Malcolm works in Data Goverance, Analytics Governance, Data Management,
Master Data Management, Data Privacy and Legal, Reference Data Management, Big Data
Management, Data-centric Development, Semantics, Ontologies, Data Architecture, Data
Modeling, Business Rules Management, End User Computing Governance, and many other
specializations in the area of data.
Malcolm has been awarded the prestigious DAMA International Professional Achievement Award
for contributions to Master Data Management and Reference Data Management.

6. www.octopai.com
Deep Dive into How Automating Data
Lineage Improves BI Performance (Cloud
Migration Use Case)

7. www.octopai.com
BI and Data Lineage
Business intelligence (BI) comprises the strategies and technologies used by enterprises for the data
analysis of business information. BI technologies provide historical, current, and predictive views
of business operations. Common functions of business intelligence technologies include reporting, online
analytical processing, analytics, dashboard development,...
h ttp s://e n .w ikip e d ia.org /w iki/Bu sin e ss_in te llig e n ce
Data Lineage is the understanding of the pathways by which data elements travel within the enterprise,
including all transformations that occur to it.
• BI an d Data Lin e ag e are in tim ate ly con n e cte d – su cce ssfu l BI d e p e n d s on h avin g g ood Data
Lin e ag e
• Th e re are m an y u se case s w e cou ld con sid e r – w e w ill look at on e in d e p th :
Clou d Mig ration

8. www.octopai.com
Manual vs. Automated Data Lineage
• Th e re are on ly a fe w op tion s for u n d e rstan d in g Data Lin e ag e
• Docu m e n tation is n e arly alw ays ou t of d ate , in com p le te , u n in te g rate d , an d at too h ig h a
le ve l of g ran u larity
• Man u al e ffort is im p ossib le . Th e re are n ot e n ou g h re sou rce s to cove r th e d om ain to b e
m ig rate d – d atab ase s, ETL, SQL Scrip ts, th e Re p ort Laye r (in clu d in g tran sform ation s) – an d
stitch in g it all tog e th e r
• Au tom ate d Data Lin e ag e h as b e com e availab le re ce n tly an d is th e on ly viab le op tion
Use Existing
Documentation
Manual Effort Automated Data
Lineage

9. www.octopai.com
Migration to the Cloud
Cloud computing is firmly established as the new normal for
enterprise IT. Across industries, cloud continues to be one of the
fastest-growing segments of IT spend. With greater spend, however,
comes greater responsibility for CIOs to invest budgets wisely, and a
bigger impact if things go wrong.
Gartner, Jan 22, 2020: https://www.gartner.com/smarterwithgartner/4-trends-impacting-cloud-adoption-in-2020/
• Mig ration to th e Clou d is h ap p e n in g to ach ie ve h u g e cost savin g s
• An d th e re are n e w BI tools in th e Clou d th at are te ch n ically su p e rior
- So th e valu e p rop osition for m ig ration is ove rw h e lm in g
• BI d e ve lop e rs w ill in e vitab ly b e in volve d in Clou d m ig ration p roje cts
• NOTE: m ig ration s h ap p e n all th e tim e d u e to te ch n olog y ch an g e s an d
Clou d m ig ration s are on ly th e late st kin d of m ig ration
- So th e le sson s le arn e d h e re w ill h e lp BI d e ve lop e rs w ith oth e r kin d s of m ig ration s
in th e fu tu re
• W h at cou ld p ossib ly g o w ron g …

10. www.octopai.com
Data cutoff –
Reroute to Cloud
Legacy
Data Flow
New Data
Flow to Cloud
Legacy Flows and
Processes to be
Migrated to Cloud
New Process
in Cloud
New Report in
Cloud
Legacy Report
Migrating Your BI Environment to the Cloud is Not So Simple
• The complexity of the task needs
to be understood quickly and up
front
• “Peel the Onion” analysis will lead
to disaster
• You can only be successful with
automated data lineage

11. www.octopai.com
The Cloud Migration Project
Assessment Project Plan Delivery
• Scop e of m ig ration
• Tool se le ction
• Tim e lin e
• Re sou rce Re q u ire m e n ts
• …
• De live rab le De fin ition
• Sp rin t P lan n in g
• Role s an d Re sp on sib ilitie s
• De p e n d e n cie s
• …
• Datab ase De sig n
• ETL De ve lop m e n t
• Re p ort De ve lop m e n t
• Cod e Fre e ze s
• …
• Th e g re ate st vu ln e rab ility of all d ata-ce n tric p roje cts is th e lack of sou rce d ata
an alysis, an d th is is ofte n lackin g in th e p lan n in g an d e xe cu tion of th e p roje ct.
• You can n ot m ig rate w h at you d o n ot kn ow ab ou t.
• How far b ack in th e d ata su p p ly ch ain d o you h ave to g o to cu t ou t w h at you
w ill tran sp lan t in to th e Clou d ?
• W h at tran sform ation s h ave to h ap p e n to th e d ata afte r it le ave s its sou rce s
an d b e fore (an d w h e n ) it g e ts in to th e BI Laye r?

12. www.octopai.com
Don ’t Move What You Don ’t Need
• Ove r tim e it is ve ry like ly th at a le g acy e n viron m e n t w ill accu m u late a lot of “d e ad w ood ”
• Ye t BI d e ve lop e rs are ofte n afraid th at th e y can n ot tru st th e ir p u re ly m an u al ju d g e m e n t
th at tab le s, colu m n s, an d ETL p roce sse s are n o lon g e r u se d .
• Au tom ate d Data Lin e ag e can p rovid e th e con fid e n ce to id e n tify th e u n u se d com p on e n ts
so th e y are n ot m ove d to th e Clou d – w h ich can b e a b ig savin g .
Column 1
Column 2
Column 3
Column 4
Column 5
Table A
Column 1
Column 2
Column 3
Column 4
Column 5
Table B
ETL
Process 1
ETL
Process 2
Table C
Column 1

13. www.octopai.com
Total Universe
Known
Universe Enterprise
Data Universe Data Store
Universe
Unknown
Universe
Potential
Data
Universe
Unneeded
Data
Universe
Required
Data
Universe
Target Data
Universe
Data Lineage Provides Information about Data Coverage
• W h e n m ig ratin g to th e Clou d it is
n e ce ssary to kn ow w h at th e
cove rag e of e ach d atase t is.
• Data Lin e ag e can p rovid e th is
in form ation b y fin d in g th e
u ltim ate sou rce s of e ach d atase t.
• Th is can also re ve al d ata
d u p lication .
• It also p rovid e s con fid e n ce th at
th e d atase ts in th e Clou d w ill
con tain th e fu ll com p le m e n t of
d ata n e e d e d for th e BI Re p orts.

14. www.octopai.com
“ Lift and Shift ” versus Process Optimization
• Elim in atin g u n u se d com p on e n ts is on e th in g , b u t ve ry ofte n th e re is a n e e d for p roce ss
re -e n g in e e rin g as w e ll.
• Som e tim e s th is is sim p ly d u e to th e te ch n olog y on th e Clou d sid e
• More m atu re e n te rp rise s u n d e rstan d th at th e m ig ration is an op p ortu n ity to op tim ize
th e ir d ata su p p ly ch ain s.
• BUT – th is all h as to b e p lan n e d from th e start. It can n ot b e d on e w ith ou t au tom ate d
Data Lin e ag e p rovid in g a d e taile d p ictu re of th e le g acy e n viron m e n t. Th is can th e n b e
in te rp re te d to facilitate th e n e w d e sig n .
• Ve ry ofte n , th e d e fau lt p osition is to “lift an d sh ift” as th is se e m s ch e ap e r an d e asie r – b u t
in th e e n d it m ay b e th e costlie st op tion .

15. www.octopai.com
Understanding Data Lineage Can Help Cloud Cost Optimization
Low Cost
$
Medium
Cost
$$
High Cost
$$$
Cloud Environment
• Kn ow in g you r d ata lin e ag e p rior to
p roje ct im p le m e n tation can b e
b e n e ficial for arch ite ctu re
• Eve n if you are ju st d oin g a “Lift an d
Sh ift” you can allocate storag e an d
p roce ssin g to Clou d se g m e n ts to
op tim ize op e ration al costs.
• Th e BI d e ve lop e rs can in te rp re t th e
d ata lin e ag e in te rm s of d ata
volu m e s an d p roce ssin g load s, an d
in form th e arch ite cts.
• Th is is a b e n e fit of au tom ate d d ata
lin e ag e th at is som e tim e s n ot
u n d e rstood .

16. www.octopai.com
Asset Control During the Project
Joe
Alice
Bob
• W ith a fu ll u n d e rstan d in g of all th e ob je cts to b e m ig rate d , at th e m ost d e taile d le ve l, it is
m u ch e asie r to d ivid e u p th e w ork to b e d on e .
• Th is also allow s for b e tte r p roje ct m an ag e m e n t
• Me trics sh ow in g p roje ct p rog re ss are e asie r to m an ag e
• Th is d e fin ite ly im p rove s BI p e rform an ce , an d in cre ase s con fid e n ce in th e ou tcom e of th e
p roje ct.

17. www.octopai.com
DATA
DATA
• Th e w orst of b oth w orld s h ap p e n s w h e n m ig ration s are in com p le te (u n p lan n e d
“h yb rid ”)
- Th e re is a lon g tran sition p h ase w h e n On -p re m ise an d Clou d coe xist
- Tim e , m on e y, p atie n ce ru n ou t an d th e m ig ration is p au se d (or e n d s)
- Un fore se e n te ch n ical an d b u sin e ss issu e s m e an th at n ot e ve ryth in g can b e m ig rate d
• Now com p le xity for BI d e ve lop m e n t an d op e ration s is m u ch g re ate r
- An d th e d ata su p p ly ch ain – d ata lin e ag e – is e xp on e n tially m ore com p le x
The Transition Phase, Building The Legacy, and What ’s Left Behind

18. www.octopai.com
Quick Review of Automated Data Lineage
in Octopai

19. The BI Intelligence Platform

20. 00
Cloud Wisdom Data Lineage
BI Catalog
Versioning
Insights
BI2 Dashboard Data Discovery
ETL DB/DWH Analysis Reporting & Analytics
Metadata Management Platform
A SaaS product that is:
• Cross platform
• Easy to start
• Simple and intuitive to use
Technology that leverages smart
algorithms and modeling to extract
all metadata types, understand
cross connections and find them
quickly

21. www.octopai.com
Questions and Answers

22. Interested in seeing a demo?
https://www.octopai.com/videos/live -demo/
OR
Get in touch for a free trial!
amnond@octopai.com
www.octopai.com