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Journey to
Marketing Data Lake
BRK1098
Oracle Modern Marketing
Experience | Las Vegas | Apr 26-28
Sumit Sarkar
Product Marketing
@SAsInSumit
linkedin.com/in/meetsumit
© 2016 Progress Software Corporation and/or its subsidiaries or affiliates. All rights reserved.2
Agenda
1. What we are trying to achieve
2. Why we built a Data Lake
3. Sample Insights
4. Good and not so good
What we are trying to achieve
© 2016 Progress Software Corporation and/or its subsidiaries or affiliates. All rights reserved.4
Progress at a Glance
EMPLOYEES ~1,800
FY15 REVENUES $412 million
Non-GAAP MARGIN 29%
RENEWAL RATES 90%+
DEVELOPER COMMUNITY 1.7 million
CUSTOMERS WORLDWIDE 140,000+ in 180
Countries
GLOBAL REVENUE STREAM 42%
APPLICATIONS DEPLOYED 30,000+
© 2016 Progress Software Corporation and/or its subsidiaries or affiliates. All rights reserved.5
Overview of my business line
© 2016 Progress Software Corporation and/or its subsidiaries or affiliates. All rights reserved.6
Need answers at marketing speed..
1. Invite contacts to our webinar who identified specific interests with active opportunities
and include related contacts to that same project?
2. Identify common ProductA pages that convert to ProductB evaluations (i.e. measure
cross sell potential)
3. What web content did the 1100 webinar attendees view following the webinar?
4. Analyze lead histories to track accuracy in lead routing assignment (Salesforce limits
values that can be reported against)
5. Identify which of our web content is most visited for sales opportunities that were
closed/won?
6. Create a list based on content consumption and 2017 survey answers?
7. What content was consumed across our strategic accounts?
8. Who complained about a broken link in the survey?
9. …
Why we built a Data Lake
© 2016 Progress Software Corporation and/or its subsidiaries or affiliates. All rights reserved.8
A data lake is a large-scale storage repository and
processing engine. A data lake provides "massive
storage for any kind of data, enormous processing
power and the ability to handle virtually limitless
concurrent tasks or jobs”
- SAS Institute
What is a Data Lake?
© 2016 Progress Software Corporation and/or its subsidiaries or affiliates. All rights reserved.9
Benefits of a Marketing Data Lake
Some of the benefits of a data lake include:
 Store data in all shapes and sizes
 Flexible analytics with “schema on read”
 Query data using SQL or big data
programming frameworks
 Eliminate data silos
 Low-cost storage for growing marketing data
sets
© 2016 Progress Software Corporation and/or its subsidiaries or affiliates. All rights reserved.11
Why Marketing Data is increasing in value?
 CMOs will outspend CIOs on technology by 2017 (Gartner)
 Oracle spent $3B on a martech acquisition spree to gain CMO
mindshare.
 Expect more collaboration between CMO and CIO (CIO.com)
In 2017, we’re going to see analytics do more than ever to drive customer satisfaction. As the world of big data
exploded, business leaders had a false comfort in having these mammoth data lakes which brought no
value on their own when they were sitting unanalyzed. Plain and simple, data tells us about our customers
— it’s how we learn more about customers and how to better serve them. As today’s customers expect a
personalized experience when interacting with a business, we’re going to see customer analytics become the spinal
cord of the customer journey, creating touch points at every level of the funnel and at every moment of interaction.
- Ketan Karkhanis, SVP and GM of the Salesforce Analytics Cloud
Eloqua analytics is awesome
© 2016 Progress Software Corporation and/or its subsidiaries or affiliates. All rights reserved.13
Eloqua Embedded Analytics
But we need analytics with other
customer and marketing data
© 2016 Progress Software Corporation and/or its subsidiaries or affiliates. All rights reserved.15
Analytics Today
Marketing
Data Management Platform
Embedded Insights
Operational Insights
Information Technology
Data Warehouse
Enterprise Reporting/Analytics
Enterprise Data Integration
LoB
Desktop Analytics / Spreadmarts
Sumologic Analytics
Mixed access to Martech/IT analytics
© 2016 Progress Software Corporation and/or its subsidiaries or affiliates. All rights reserved.16
Thus, we embarked on a Data Lake for Progress
 Detailed data such as activities in Eloqua were
not suitable to store in Corporate Data
Warehouse or Marketing DMP
 Data fragmented across sales CRM and
service CX; marketing automation; web
analytics; usage for cloud apps; survey
platforms; webinar data, etc
 Did not know what questions to ask in advance
– how to define star schema?
 Many analytics tools across Progress
 Emerging data science expertise
 Started with Pilot to start experimenting rather
than wait to build a business case for funding
Data Collection Process
© 2016 Progress Software Corporation and/or its subsidiaries or affiliates. All rights reserved.18
© 2016 Progress Software Corporation and/or its subsidiaries or affiliates. All rights reserved.19
Sample Data: Oracle Eloqua Profiler data
© 2016 Progress Software Corporation and/or its subsidiaries or affiliates. All rights reserved.20
Sample Data: CRM
© 2016 Progress Software Corporation and/or its subsidiaries or affiliates. All rights reserved.21
Sample Data: Web traffic
© 2016 Progress Software Corporation and/or its subsidiaries or affiliates. All rights reserved.22
Sample Data: Survey
Other popular responses
Linode
Pironet
Redhat OpenShift
OpenStack
Cloud Share
Thomson Reuters Elektron
SAP HANA
Claro Cloud
© 2016 Progress Software Corporation and/or its subsidiaries or affiliates. All rights reserved.23
Not trivial to get data across different marketing data sources
Data Source API
Eloqua Web Services API (REST/SOAP)
Bulk and non-Bulk APIs
No query language
Oracle Service Cloud Web Services APIs (REST/SOAP)
ROQL
Google Analytics Hypercube (query limits of 10 metrics grouped by
max of 7 dimensions)
Veeva CRM SOAP, BULK, Metadata APIs
SOQL
© 2016 Progress Software Corporation and/or its subsidiaries or affiliates. All rights reserved.24
Overview of Progress Marketing Data Lake
Progress Corporate Firewall
[Roadmap]
© 2016 Progress Software Corporation and/or its subsidiaries or affiliates. All rights reserved.25
Sample Eloqua Objects/Fields in Data Lake Schema
Approximate Object sizes in April 2017
Emailsend: 63 GB*
Pageview: 42 GB*
Salesforce Lead history: 21 GB
* Growing at ~20-25 GB / yr
© 2016 Progress Software Corporation and/or its subsidiaries or affiliates. All rights reserved.26
Geek Bits
Database: Apache Hadoop (cluster has 4 nodes with 16TB of disk space)
Interfaces: Hive 1.2.1 and Spark 2.0.0
Tuning: Apache Tez Execution Engine with ORC file storage format
Data Loader: Apache Sqoop
Data Access: Oracle Eloqua, Google Analytics and Salesforce JDBC connectors with the
DataDirect Cloud service for use with Apache Sqoop
Initial load size: 96 GB
Sample Sqoop Scripts located here.
© 2016 Progress Software Corporation and/or its subsidiaries or affiliates. All rights reserved.27
Connection Information for both Casual and Power Users
Host: bigdata01
Port: 10000
Login: <username>/<password>
Schema datalake
Sample Insights
© 2016 Progress Software Corporation and/or its subsidiaries or affiliates. All rights reserved.29
Is it creepy?
© 2016 Progress Software Corporation and/or its subsidiaries or affiliates. All rights reserved.30
Sample Insights: Trends in 2016 for product usage following related events
March &
September
June
© 2016 Progress Software Corporation and/or its subsidiaries or affiliates. All rights reserved.31
Sample Insights: Data Lake Insights
Knowledge Articles from Evaluation Leads
Fix in Apache Hive ODBC 07.11.0081 (B0058, U0037)
http://knowledgebase.progress.com/articles/Article/General-error-Thrift-protocol-using-unversioned-
messages-error-with-Apache-Hive-ODBC-driver
© 2016 Progress Software Corporation and/or its subsidiaries or affiliates. All rights reserved.32
Sample Insights: How well is our content resonating for select lead queues in
SFDC?
© 2016 Progress Software Corporation and/or its subsidiaries or affiliates. All rights reserved.33
Sample Insights: Identify journey based segmentation such as stage of product
evaluation
Measure success of product evaluations by analyzing patterns of activity data using advanced analytics techniques
© 2016 Progress Software Corporation and/or its subsidiaries or affiliates. All rights reserved.34
Sample Insights: Making a second impression after 404 errors on PPC
It was reported by a PPC lead prospect that our url to evaluate the product had appended ?gclid preventing the trial to
start and there was no record in Google Analytics. We were able to pull the list of contacts who had this issue from
the data lake based on SFDC lead and Eloqua activity URL to send an apology with the correct url, and exclude
those already engaged in active sales cycle.
Good and not so Good
© 2016 Progress Software Corporation and/or its subsidiaries or affiliates. All rights reserved.36
Good
Building advocacy for
marketing data
Brought together several teams across Product, Sales, Marketing
Operations, Engineering, and others interested in the data
available for analysis.
Revenue attribution to content using activity data correlated across
opportunities and content consumed.
Analyze detailed CRM lead histories to measure lead routing
effectiveness. Salesforce reports do not support analysis on
values of detailed lead activity fields.
Able to leverage SMEs to identify laser focused targets. I.e. which
leads have the specific tech stack that the next webinar is
targeting.
Trends and Research
Supplement existing
CRM analytics
Identify new and highly
focused segments
© 2016 Progress Software Corporation and/or its subsidiaries or affiliates. All rights reserved.37
Not as Good
Infrastructure
On-premises Hadoop cluster was not ideal for LoB to manage and
tune for the pilot, but we did not have approval to land LOB data in
the cloud. Need additional support to go live.
Data lake dumps raw data from source systems, so we end up
with activity from automated tests that can skew data, for example.
We did not catalog the data imported and count on the naming
conventions of the source systems to describe the data.
Growing data science practice across Progress, but few resources
in my LoB for statistical analysis and prediction.
Data Quality
Metadata
Data Science
© 2016 Progress Software Corporation and/or its subsidiaries or affiliates. All rights reserved.38
Roadmap
Sumit Sarkar
Product Marketing
@SAsInSumit
linkedin.com/in/meetsumit
© 2016 Progress Software Corporation and/or its subsidiaries or affiliates. All rights reserved.39
Learn more from Progress Marketing Ops tomorrow …
Ten Oracle Eloqua Hacks That Will Turn You into a Modern Marketing Magician
[THT1316]
Laura Lewis, Customer Journey Manager, Progress Software
Carmen Gardiner, Marketing Ops, Progress
Have you ever been so good at something that people think what you do is magic? True
experts know that the key is thinking outside of the box—using Oracle Eloqua’s vast
capabilities in new and innovative ways to achieve goals others have never even thought of.
How do you track Google AdWords past page views? How do you segment for true account-
based marketing? What can you do to ensure that your emails don’t end up on Gmail’s
Promotions tab? This session is for those problem-solvers who aren’t afraid to get their hands
dirty and see how Oracle Eloqua can be extended to solve today’s modern marketing
problems. You’ll find out how to use Oracle Eloqua in new and unexpected ways to achieve
seemingly impossible results—making you indispensable as a true modern marketing
magician.
Theater
Thursday, Apr 27, 12:40 p.m. | Modern Marketing Theater
Journey to Marketing Data Lake [BRK1098]

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Journey to Marketing Data Lake [BRK1098]

  • 1. Journey to Marketing Data Lake BRK1098 Oracle Modern Marketing Experience | Las Vegas | Apr 26-28 Sumit Sarkar Product Marketing @SAsInSumit linkedin.com/in/meetsumit
  • 2. © 2016 Progress Software Corporation and/or its subsidiaries or affiliates. All rights reserved.2 Agenda 1. What we are trying to achieve 2. Why we built a Data Lake 3. Sample Insights 4. Good and not so good
  • 3. What we are trying to achieve
  • 4. © 2016 Progress Software Corporation and/or its subsidiaries or affiliates. All rights reserved.4 Progress at a Glance EMPLOYEES ~1,800 FY15 REVENUES $412 million Non-GAAP MARGIN 29% RENEWAL RATES 90%+ DEVELOPER COMMUNITY 1.7 million CUSTOMERS WORLDWIDE 140,000+ in 180 Countries GLOBAL REVENUE STREAM 42% APPLICATIONS DEPLOYED 30,000+
  • 5. © 2016 Progress Software Corporation and/or its subsidiaries or affiliates. All rights reserved.5 Overview of my business line
  • 6. © 2016 Progress Software Corporation and/or its subsidiaries or affiliates. All rights reserved.6 Need answers at marketing speed.. 1. Invite contacts to our webinar who identified specific interests with active opportunities and include related contacts to that same project? 2. Identify common ProductA pages that convert to ProductB evaluations (i.e. measure cross sell potential) 3. What web content did the 1100 webinar attendees view following the webinar? 4. Analyze lead histories to track accuracy in lead routing assignment (Salesforce limits values that can be reported against) 5. Identify which of our web content is most visited for sales opportunities that were closed/won? 6. Create a list based on content consumption and 2017 survey answers? 7. What content was consumed across our strategic accounts? 8. Who complained about a broken link in the survey? 9. …
  • 7. Why we built a Data Lake
  • 8. © 2016 Progress Software Corporation and/or its subsidiaries or affiliates. All rights reserved.8 A data lake is a large-scale storage repository and processing engine. A data lake provides "massive storage for any kind of data, enormous processing power and the ability to handle virtually limitless concurrent tasks or jobs” - SAS Institute What is a Data Lake?
  • 9. © 2016 Progress Software Corporation and/or its subsidiaries or affiliates. All rights reserved.9 Benefits of a Marketing Data Lake Some of the benefits of a data lake include:  Store data in all shapes and sizes  Flexible analytics with “schema on read”  Query data using SQL or big data programming frameworks  Eliminate data silos  Low-cost storage for growing marketing data sets
  • 10.
  • 11. © 2016 Progress Software Corporation and/or its subsidiaries or affiliates. All rights reserved.11 Why Marketing Data is increasing in value?  CMOs will outspend CIOs on technology by 2017 (Gartner)  Oracle spent $3B on a martech acquisition spree to gain CMO mindshare.  Expect more collaboration between CMO and CIO (CIO.com) In 2017, we’re going to see analytics do more than ever to drive customer satisfaction. As the world of big data exploded, business leaders had a false comfort in having these mammoth data lakes which brought no value on their own when they were sitting unanalyzed. Plain and simple, data tells us about our customers — it’s how we learn more about customers and how to better serve them. As today’s customers expect a personalized experience when interacting with a business, we’re going to see customer analytics become the spinal cord of the customer journey, creating touch points at every level of the funnel and at every moment of interaction. - Ketan Karkhanis, SVP and GM of the Salesforce Analytics Cloud
  • 13. © 2016 Progress Software Corporation and/or its subsidiaries or affiliates. All rights reserved.13 Eloqua Embedded Analytics
  • 14. But we need analytics with other customer and marketing data
  • 15. © 2016 Progress Software Corporation and/or its subsidiaries or affiliates. All rights reserved.15 Analytics Today Marketing Data Management Platform Embedded Insights Operational Insights Information Technology Data Warehouse Enterprise Reporting/Analytics Enterprise Data Integration LoB Desktop Analytics / Spreadmarts Sumologic Analytics Mixed access to Martech/IT analytics
  • 16. © 2016 Progress Software Corporation and/or its subsidiaries or affiliates. All rights reserved.16 Thus, we embarked on a Data Lake for Progress  Detailed data such as activities in Eloqua were not suitable to store in Corporate Data Warehouse or Marketing DMP  Data fragmented across sales CRM and service CX; marketing automation; web analytics; usage for cloud apps; survey platforms; webinar data, etc  Did not know what questions to ask in advance – how to define star schema?  Many analytics tools across Progress  Emerging data science expertise  Started with Pilot to start experimenting rather than wait to build a business case for funding
  • 18. © 2016 Progress Software Corporation and/or its subsidiaries or affiliates. All rights reserved.18
  • 19. © 2016 Progress Software Corporation and/or its subsidiaries or affiliates. All rights reserved.19 Sample Data: Oracle Eloqua Profiler data
  • 20. © 2016 Progress Software Corporation and/or its subsidiaries or affiliates. All rights reserved.20 Sample Data: CRM
  • 21. © 2016 Progress Software Corporation and/or its subsidiaries or affiliates. All rights reserved.21 Sample Data: Web traffic
  • 22. © 2016 Progress Software Corporation and/or its subsidiaries or affiliates. All rights reserved.22 Sample Data: Survey Other popular responses Linode Pironet Redhat OpenShift OpenStack Cloud Share Thomson Reuters Elektron SAP HANA Claro Cloud
  • 23. © 2016 Progress Software Corporation and/or its subsidiaries or affiliates. All rights reserved.23 Not trivial to get data across different marketing data sources Data Source API Eloqua Web Services API (REST/SOAP) Bulk and non-Bulk APIs No query language Oracle Service Cloud Web Services APIs (REST/SOAP) ROQL Google Analytics Hypercube (query limits of 10 metrics grouped by max of 7 dimensions) Veeva CRM SOAP, BULK, Metadata APIs SOQL
  • 24. © 2016 Progress Software Corporation and/or its subsidiaries or affiliates. All rights reserved.24 Overview of Progress Marketing Data Lake Progress Corporate Firewall [Roadmap]
  • 25. © 2016 Progress Software Corporation and/or its subsidiaries or affiliates. All rights reserved.25 Sample Eloqua Objects/Fields in Data Lake Schema Approximate Object sizes in April 2017 Emailsend: 63 GB* Pageview: 42 GB* Salesforce Lead history: 21 GB * Growing at ~20-25 GB / yr
  • 26. © 2016 Progress Software Corporation and/or its subsidiaries or affiliates. All rights reserved.26 Geek Bits Database: Apache Hadoop (cluster has 4 nodes with 16TB of disk space) Interfaces: Hive 1.2.1 and Spark 2.0.0 Tuning: Apache Tez Execution Engine with ORC file storage format Data Loader: Apache Sqoop Data Access: Oracle Eloqua, Google Analytics and Salesforce JDBC connectors with the DataDirect Cloud service for use with Apache Sqoop Initial load size: 96 GB Sample Sqoop Scripts located here.
  • 27. © 2016 Progress Software Corporation and/or its subsidiaries or affiliates. All rights reserved.27 Connection Information for both Casual and Power Users Host: bigdata01 Port: 10000 Login: <username>/<password> Schema datalake
  • 29. © 2016 Progress Software Corporation and/or its subsidiaries or affiliates. All rights reserved.29 Is it creepy?
  • 30. © 2016 Progress Software Corporation and/or its subsidiaries or affiliates. All rights reserved.30 Sample Insights: Trends in 2016 for product usage following related events March & September June
  • 31. © 2016 Progress Software Corporation and/or its subsidiaries or affiliates. All rights reserved.31 Sample Insights: Data Lake Insights Knowledge Articles from Evaluation Leads Fix in Apache Hive ODBC 07.11.0081 (B0058, U0037) http://knowledgebase.progress.com/articles/Article/General-error-Thrift-protocol-using-unversioned- messages-error-with-Apache-Hive-ODBC-driver
  • 32. © 2016 Progress Software Corporation and/or its subsidiaries or affiliates. All rights reserved.32 Sample Insights: How well is our content resonating for select lead queues in SFDC?
  • 33. © 2016 Progress Software Corporation and/or its subsidiaries or affiliates. All rights reserved.33 Sample Insights: Identify journey based segmentation such as stage of product evaluation Measure success of product evaluations by analyzing patterns of activity data using advanced analytics techniques
  • 34. © 2016 Progress Software Corporation and/or its subsidiaries or affiliates. All rights reserved.34 Sample Insights: Making a second impression after 404 errors on PPC It was reported by a PPC lead prospect that our url to evaluate the product had appended ?gclid preventing the trial to start and there was no record in Google Analytics. We were able to pull the list of contacts who had this issue from the data lake based on SFDC lead and Eloqua activity URL to send an apology with the correct url, and exclude those already engaged in active sales cycle.
  • 35. Good and not so Good
  • 36. © 2016 Progress Software Corporation and/or its subsidiaries or affiliates. All rights reserved.36 Good Building advocacy for marketing data Brought together several teams across Product, Sales, Marketing Operations, Engineering, and others interested in the data available for analysis. Revenue attribution to content using activity data correlated across opportunities and content consumed. Analyze detailed CRM lead histories to measure lead routing effectiveness. Salesforce reports do not support analysis on values of detailed lead activity fields. Able to leverage SMEs to identify laser focused targets. I.e. which leads have the specific tech stack that the next webinar is targeting. Trends and Research Supplement existing CRM analytics Identify new and highly focused segments
  • 37. © 2016 Progress Software Corporation and/or its subsidiaries or affiliates. All rights reserved.37 Not as Good Infrastructure On-premises Hadoop cluster was not ideal for LoB to manage and tune for the pilot, but we did not have approval to land LOB data in the cloud. Need additional support to go live. Data lake dumps raw data from source systems, so we end up with activity from automated tests that can skew data, for example. We did not catalog the data imported and count on the naming conventions of the source systems to describe the data. Growing data science practice across Progress, but few resources in my LoB for statistical analysis and prediction. Data Quality Metadata Data Science
  • 38. © 2016 Progress Software Corporation and/or its subsidiaries or affiliates. All rights reserved.38 Roadmap Sumit Sarkar Product Marketing @SAsInSumit linkedin.com/in/meetsumit
  • 39. © 2016 Progress Software Corporation and/or its subsidiaries or affiliates. All rights reserved.39 Learn more from Progress Marketing Ops tomorrow … Ten Oracle Eloqua Hacks That Will Turn You into a Modern Marketing Magician [THT1316] Laura Lewis, Customer Journey Manager, Progress Software Carmen Gardiner, Marketing Ops, Progress Have you ever been so good at something that people think what you do is magic? True experts know that the key is thinking outside of the box—using Oracle Eloqua’s vast capabilities in new and innovative ways to achieve goals others have never even thought of. How do you track Google AdWords past page views? How do you segment for true account- based marketing? What can you do to ensure that your emails don’t end up on Gmail’s Promotions tab? This session is for those problem-solvers who aren’t afraid to get their hands dirty and see how Oracle Eloqua can be extended to solve today’s modern marketing problems. You’ll find out how to use Oracle Eloqua in new and unexpected ways to achieve seemingly impossible results—making you indispensable as a true modern marketing magician. Theater Thursday, Apr 27, 12:40 p.m. | Modern Marketing Theater

Editor's Notes

  1. The challenge this session’s speaker and his colleagues faced in trying to learn more about customer experiences was that insights are fragmented across different systems such as Oracle Eloqua, CRM, and web analytics. To better understand their contacts, they started with the corporate data warehouse, which was missing a lot of this lower-value and detailed data. When they considered expanding the data warehouse, it was difficult to define what questions they wanted to answer in advance, because it varies for each campaign they run. Thus they embarked on building a Hadoop-based data lake, for the flexibility to ask any questions with an ad hoc schema on read approach, against any customer data sets in varying levels of detail, to better understand what their visitors want to consume. Breakout Session Wednesday, Apr 26, 5:45 p.m. | Mandalay Bay D Pillar: Marketing Marketing Track: Data-Driven Marketing Product: Oracle Data Management Platform (Oracle BlueKai) Level: Intermediate Session Type: Breakout Session https://go.oracle.com/moderncx-speaker-information https://oracle.rainfocus.com/scripts/catalog/oracleCx17.jsp?search=BRK1098
  2. Data Lakes are loaded with raw data (no “T”) and create the “Schema on Read” on business demand
  3. To really get big data value, you need to store all types of structured and semi-structured data in a data lake, from CRM data, to social media posts. You don’t have to have all the answers upfront, or even the questions. Lakes store raw data that can be transformed as questions arise. Use a variety of tools based on what you’re asking. Everyone talks about a single, unified view of data http://info.zaloni.com/hubfs/Architecting_Data_Lakes_Zaloni.pdf By Ben Sharma and Alice LaPlante
  4. Source: http://www.cio.com/article/2825086/cio-role/is-the-cio-cmo-transition-of-power-becoming-a-reality.html
  5. 1200 respondents telling us what they use!
  6. Resources: Masters in CompSci from local University Time: 2-3 weeks with D2C service
  7. 2013 – pageviews 2015 – pagevisits 2010 - emailsends
  8. The project is still run by marketing engineers, so we don’t get the perks of an IT driven project. We expect to continue expanding use and value to then elevate this to production and start looking to do more buying than building. Statistical analysis of detailed data Log data to study application characteristics Performance lab data
  9. The project is still run by marketing engineers, so we don’t get the perks of an IT driven project. We expect to continue expanding use and value to then elevate this to production and start looking to do more buying than building. Statistical analysis of detailed data Log data to study application characteristics Performance lab data