The average age of a company listed on the S&P 500 has fallen from almost 60 years old in the 1950s to less than 20 years old today. Innovative companies that are willing to embrace transformative technologies make the list today, while businesses that are hesitant to embrace change risk becoming obsolete. Innovators use big data solutions as a competitive advantage to increase revenue, reduce cost, and improve cash flow. Turn big data into actionable insights with Oracle Analytics Cloud. We identified the big data opportunities in front of you and how to take advantage of them: -Big data and its architecture -Why a big data strategy is imperative to remaining relevant -How Oracle Analytics Cloud can help you connect people, places, data, and systems to fundamentally change how you analyze, understand, and act on information

1. How to Capitalize on Big Data
with Oracle Analytics Cloud
June, 2018

2. Shiv Bharti
Practice Director,
Oracle Business Analytics
shiv.bharti@perficient.com
Mazen Manasseh
Senior Solutions Architect,
Oracle Business Analytics
Mazen.manasseh@perficient.com

3. 3
Agenda
• About Perficient
• Opportunity
• Technical Use Cases
• Business Use Cases
• Big Data Architecture
• Oracle Big Data Strategy and Cloud
• Which Oracle Cloud Services to Choose
• Implementation Approach
• OAC and Data Lake
• Q&A

4. 4
About Perficient
Perficient is the leading digital transformation
consulting firm serving Global 2000
and enterprise customers throughout
North America.
With unparalleled information technology, management
consulting, and creative capabilities, Perficient and its
Perficient Digital agency deliver vision, execution, and
value with outstanding digital experience, business
optimization, and industry solutions.

5. 5
Perficient Profile
• Founded in 1997
• Public, NASDAQ: PRFT
• 2017 revenue $485 million
• Major market locations:
Allentown, Atlanta, Ann Arbor, Boston, Charlotte,
Chicago, Cincinnati, Columbus, Dallas, Denver, Detroit,
Fairfax, Houston, Indianapolis, Lafayette, Milwaukee,
Minneapolis, New York City, Northern California, Oxford
(UK), Phoenix, Seattle, Southern California, St. Louis,
Toronto, Washington, D.C.
• Global delivery centers in China, India and Mexico
• 3,000+ colleagues
• Dedicated solution practices
• ~95% repeat business rate
• Alliance partnerships with major technology vendors
• Multiple vendor/industry technology and growth
awards

6. 6
Perficient’s Oracle BI Practice
Fast Facts
• Practice Started: 2004
• Projects Completed: 400+
• Management Team: 14 years
• 60% of consultants former Oracle Eng.
• Oracle authorized education center
• Oracle BI Apps, OBIEE, ODI
• Perficient runs it’s business on Oracle BI
Solutions Expertise
• BI/DW strategy and assessments
• OBIEE and Oracle BI Apps
• Cloud & on-premises solutions
• Custom data warehouse services
• Master Data Management
• Data integration, discovery, big data
• Exadata & Exalytics
• Oracle Golden Gate
Oracle Specializations

7. Opportunity

8. 8
Opportunity is Well Known
• Data is the fabric of every organization
• 10X return on analytics investment
• $430B advantage to those who
analyze all data and deliver
actionable insights
Opportunity

9. 9
of companies will
be investing in
predictive and
prescriptive
analytics
40%
Copyright © 2018, Oracle
Source: Forrester
• Data growth is driving complexity
– Data is doubling every 2 years
• Digital transformation is critical to success
– Emerging technologies driving need to stay
competitive
• Data science is key to innovation
– Machine learning and AI a new norm
Data-Driven Businesses Are Winning
Business is Changing

10. 10
Organizations Want To
• Access all data
– Structured, semi-structured, batch, real-time
• Innovate using data science
– Machine Learning, AI
• Build Data-Driven Solutions
– Smart, adaptive
• Data to inform every decision, every minute in every moment
that matters
• Analytic system that can interrupt consumers with relevant
insights
want scalable platform for
Data Science
35%
Source: IDC
Copyright © 2018, Oracle

11. Technical Use Cases for a
Modern Data Platform

12. 12
Data Integration from Any Source
• Data transformation / preparation
• Data replication
• Data quality
Social, IoT, more…
SaaS
Transactional
…make it accessible
Data Lake
Copyright © 2018, Oracle

13. 13
• Offload data from data warehouse
• Process data in the data lake for the
data warehouse
• Load data products to data warehouse
Complete Data Management
Data Lake
…including data in motion
Data Warehouse
NoSQL
Copyright © 2018, Oracle

14. 14
Streaming Data
Data streams
Analysis
Transformations
Data Lake
…from any source
• Event streams
• Stream processing
• Stream analytics
Copyright © 2018, Oracle

15. 15
Accelerating Data Lake Queries At Scale
• 10X to 100X faster
• Accelerates any tool
• Scale out with increased data or users
• Work with the original data,
not pre-aggregates
Data Lake
…in different locations
Data Science SQL Analytics
In-memory
• Indexing
• Cache
• Query
optimization
Copyright © 2018, Oracle

16. 16
Data Catalog
Catalog
Data Lake
…and apply data
science
• What data is available?
• Who owns the data?
• Where did it come from?
• Intelligent recommendations
Copyright © 2018, Oracle

17. Business Use Cases for a
Modern Data Platform

18. 18
Use Case:
Customer Segmentation
& Offers
Increase agility and reduce response
times to improve customer engagement
and satisfaction
Marketing teams can dynamically target messaging and
adjust outreach frequency based on variable data.
For example, retailers can create hyper-targeted
campaigns to users based on location and weather
conditions. Marketers can quickly adjust these
campaign parameters if a new line of apparel is
released.

19. 19
Use Case:
Customer-Centric
Analytics
Real-time insights and seamless
integration across channels taking lead
with loyalty, efficiency, and agility
Email Marketing - Targeted discounts at key moments in
the lifecycle, and to select customer segments, to deepen
brand relationships.
OmniChannel Marketing - Single, unified view of the
customer -- and seamless user experience -- across
channels. Ability to tailor communication on one platform
to a user’s engagement on another.
Predictive Marketing - Predicting customer lifetime value
(CLV) based on a customer’s first purchased product or
acquisition channel; identifying which customers are most
likely to churn.

20. 20
Use Case:
Operational Efficiency -
Lower Cost and Drive Growth
 Improve performance of existing
internal processes across business
operations, IT, development &
testing
 Optimize supply chain including
inventory management
 Accelerate regulatory compliance
reporting, days to minutes

21. 21
Use Case:
Predictive Maintenance
Machine Learning - Neural Networks
Using neural networks to predict attributes
of the performance of a pump. This might be
part of a predictive maintenance use case,
where an organization is looking to prevent
mechanical failures, or issues that impact
production of some chemical.

22. What Does a Typical Big Data
Architecture Consist of?

23. 23
What are Common Data Lake Technologies?
Data
Integration
Presentation &
Machine Learning
Storage
Access &
Processing
SQL StreamingBatch
ODBC, JDBC ETL, Sqoop, Hive, REST Kafka, Flume
RDBMS HDFS (Hadoop File System)NoSQL
HBase
Data Warehouse Object Storage
SQL StreamingBatch
ODBC, JDBC Pig, Hive,
MapReduce
Spark, Impala
Mahout
Python
R
Zeppelin
Flink Operational &
Platform Services
Hue
Oozie
Zookeper
YARN
Ambari
Job Scheduler
Sentry

24. 24
Classical BI vs. Big Data Analytics
Volume of data and a different type of business need
demand a non-conventional design approach.
Classic Analytics
Schema on Write
Big Data Analytics
Schema on Read
Sources
ETL to
Schema
Store (EDW) Analyze
Sources
Store
(Hadoop)
Code to
Schema Analyze

25. 25
Classical BI vs. Big Data Analytics
Volume of data and a different type of business need
demand a non-conventional design approach.
Classic Analytics
Schema on Write
Big Data Analytics
Schema on Read
Sources
ETL to
Schema
Store (EDW) Analyze
Sources
Store
(Hadoop)
Code to
Schema Analyze

26. 26
Challenges of Analyzing Diverse Data
Organizations
need to cope with
diverse data
 One solution to
access all types of
data
Big Data
technology is
fragmented and
complex with
many platform
 Leverage
emerging
technology in a
single unified
platform
Specialized skills
are in short supply
 Empower
Business Users to
self-serve and
achieve their goals

27. 27
Challenges of Analyzing Diverse Data
Organizations
need to cope with
diverse data
 One solution to
access all types of
data
Big data
technology is
fragmented and
complex with
many platform
 Leverage
emerging
technology in a
single unified
platform
Specialized skills
are in short supply
 Empower
Business Users to
self-serve and
achieve their goals

28. 28
Challenges of Analyzing Diverse Data
Organizations
need to cope with
diverse data
 One solution to
access all types of
data
Big data
technology is
fragmented and
complex with
many platform
 Leverage
emerging
technology in a
single unified
platform
Specialized skills
are in short supply
 Empower
business users to
self-serve and
achieve their goals

29. Oracle Big Data Strategy
& Cloud Service Offerings

30. 30
Oracle Information Management Services
Oracle IDCS
Identity &
Access
Management
Oracle
VPNaaS
Oracle Object
Storage Cloud
Oracle Cloud Infrastructure
text
Structured Data Semi-structured Data Unstructured Data
devices
logs
sensors
IoTLinkedInFacebook
Google
Analytics
Twitter Social Media thingsEnterprise data
ERP HCMCX
POS
Planning
Transactions
videoaudio

31. 31
Oracle Information Management Services
Oracle IDCS
Identity &
Access
Management
Oracle Event Hub Cloud
Oracle
VPNaaS
Oracle Object
Storage Cloud
Oracle
DataSync
Oracle Cloud Infrastructure
Oracle Data Integrator (ODI)
Golden Gate
text
Structured Data Semi-structured Data Unstructured Data
devices
logs
sensors
IoTLinkedInFacebook
Google
Analytics
Twitter Social Media thingsEnterprise data
ERP HCMCX
POS
Planning
Transactions
videoaudio

32. 32
Oracle Big Data
Cloud Service
(BDCS)
Oracle Information Management Services
Oracle Autonomous
Data Warehouse
Cloud Service (ADWC)
Oracle IDCS
Identity &
Access
Management
Oracle Event Hub Cloud
Oracle
VPNaaS
Oracle Object
Storage Cloud
Oracle
NoSQL
Database
Oracle
DataSync
Oracle Cloud Infrastructure
Oracle Data Integrator (ODI)
Golden Gate
text
Structured Data Semi-structured Data Unstructured Data
devices
logs
sensors
IoTLinkedInFacebook
Google
Analytics
Twitter Social Media thingsEnterprise data
ERP HCMCX
POS
Planning
Transactions
videoaudio

33. 33
Oracle Big Data
Cloud Service
(BDCS)
Oracle Information Management Services
Oracle Autonomous
Data Warehouse
Cloud Service (ADWC)
Oracle IDCS
Identity &
Access
Management
Oracle Event Hub Cloud
Oracle
VPNaaS
Oracle Object
Storage Cloud
Oracle
NoSQL
Database
Oracle
DataSync
Oracle Cloud Infrastructure
Oracle Data Integrator (ODI)
Golden Gate
O r a c l e B i g D a t a S Q L C l o u d
text
Structured Data Semi-structured Data Unstructured Data
devices
logs
sensors
IoTLinkedInFacebook
Google
Analytics
Twitter Social Media thingsEnterprise data
ERP HCMCX
POS
Planning
Transactions
videoaudio

34. 34
Oracle Big Data
Cloud Service
(BDCS)
Oracle Information Management Services
Oracle Autonomous
Data Warehouse
Cloud Service (ADWC)
Oracle IDCS
Identity &
Access
Management
Oracle Event Hub Cloud
Oracle Analytics Cloud (OAC)
Oracle
VPNaaS
Oracle Object
Storage Cloud
Oracle
NoSQL
Database
Oracle
DataSync
Oracle Cloud Infrastructure
Oracle Data Integrator (ODI)
Golden Gate
O r a c l e B i g D a t a S Q L C l o u d
text
Structured Data Semi-structured Data Unstructured Data
devices
logs
sensors
IoTLinkedInFacebook
Google
Analytics
Twitter Social Media thingsEnterprise data
ERP HCMCX
POS
Planning
Transactions
videoaudio

35. 35
Oracle Event Hub Cloud Service
Use Oracle Event Hub Cloud Service to ingest streaming data.
• Based on an Open Source Apache Kafka technology
• Extremely low latency and high throughput stream analytics platform
• Hosted and managed by Oracle Cloud
• Can create dedicated Kafka clusters
• Create Kafka Topics and start streaming data using Kafka, REST
and Stream Java APIs
• Native integration with Oracle Big Data Stack and other Cloud Apps
Event
Hub
Cloud
ODI
Cloud
Big Data
Cloud
Service
Big
Data
SQL
OAC

36. 36
Oracle Data Integrator for Big Data
ODI for Big Data helps transform and enrich data within the big data
lake without developers having to learn the languages necessary to manipulate
them.
• ODI for Big Data leverages a familiar graphical interface to generate
complex Hadoop native code
• Transformation and data movement logic is pushed down to run directly in
Hadoop.
• Optimizes developer productivity and allows ODI users to build business
and data mappings without having to learn big data languages like HiveQL,
Pig, and Map Reduce.
• Easily move data among different platforms: e.g.: from HBase to Oracle
Database, HBase to Hive, Hadoop to third-party databases and from third-
party databases to HDFS, etc.
Event
Hub
Cloud
ODI
Cloud
Big Data
Cloud
Service
Big
Data
SQL
OAC

37. 37
Oracle Big Data Cloud Service
Big data platform (PaaS) designed for the enterprise and combines Open
Source technologies with Oracle Cloud innovations:
• Leverages pre-configured Cloudera’s distribution of Apache Hadoop and
Spark
• Has the latest advances in the Hadoop ecosystem
• Provides the latest big data analytical tools, automatically installed and
configured for best performance
• Stream processing
• Apache Spark for Machine Learning
• Cloudera Impala for Ad-hoc querying
• Includes Big Data pre-configured components
• Spatial for scalable geo-spacial and map-building
• Graph for storage and analysis of social and IoT networks
• R Advanced Analytics for Apache Hadoop and Spark
• Big data connectors to simplify integration
Event
Hub
Cloud
ODI
Cloud
Big Data
Cloud
Service
Big
Data
SQL
OAC

38. 38
Oracle Big Data Cloud Service
File System
(HDFS)
NoSQL
(HBase)
Visualization & Analysis
Oracle R, Spatial, Graph, Notebook (Zeppelin)
Big data
connectors to
extract Hadoop
data to external
systems
• SQL Connector
• Loader
• XQuery
• R
• ODI
Oracle Data
Integrator
(ODI)
for
Hadoop
Workload
Orchestration
Big Data Storage
Cloudera Hadoop Enterprise
Cloudera Manager
backup, recovery, Cloudera navigator
Event
Hub
Cloud
ODI
Cloud
Big Data
Cloud
Service
Big
Data
SQL
OAC

39. 39
Oracle Big Data SQL Cloud Service
Allows joining enterprise data that resides in relational databases and data
warehouses with Oracle Big Data.
• Seamlessly use SQL query to integrate data from Hadoop, NoSQL, and
Oracle Database
• Simplifies data science efforts
• Makes big data available into the hands of more data consumers
• Facilitates the integration of big data into existing applications
• Extends Oracle database security features to data in Hadoop
Event
Hub
Cloud
ODI
Cloud
Big Data
Cloud
Service
Big
Data
SQL
OAC

40. 40
Oracle Analytics Cloud
Single platform to ingest, transform and access all Information
Event
Hub
Cloud
ODI
Cloud
Big Data
Cloud
Service
Big
Data
SQL
OAC
Data Access
• Visualizations, dashboards, self-service discovery, Day by Day mobile app
• Pixel-perfect reporting
Transformation & Data Modeling
• Data flows to ingest, blend, prepare, and store data
• Transformation at scale with Apache Spark or Oracle DB
• Single source of truth for enterprise data using a well-governed semantic layer
• High-performance, pre-calculated aggregations with Essbase Cubes
Big Data Connectors & Built-in Adapters
• Out-of-the-box integrations with Oracle Big Data stack
• High-performance data movement between relational databases and big data
Clusters using Hive, Spark-SQL, Spark and/or Map-Reduce
• Various Sources: SaaS Apps, DBs, NoSQL, and generic ODBC/JDBC

41. 41
Oracle Analytics Cloud Editions
* This is not the data lake itself, but it has capabilities to create and manage the data
lake. The Data Lake itself is another platform either an on-prem data lake or a Big Data
Cloud Service.
Functionality Standard
Edition
Data Lake
Edition*
Enterprise
Edition
Data Visualization
Self-service Data Preparation
Essbase Cloud
Big Data Sources
Data Lake Visual Discovery
Data Preparation at Scale in Spark
Enterprise Data Modeling
Enterprise Reporting (OBIEE Style)
Event
Hub
Cloud
ODI
Cloud
Big Data
Cloud
Service
Big
Data
SQL
OAC

42. Which Oracle Cloud Service
to Chose?

43. 43
Oracle Big Data
Cloud Service
(BDCS)
Data Engineering Services
Oracle Autonomous
Data Warehouse
Cloud Service (ADWC)
Oracle IDCS
Identity &
Access
Management
Oracle Event Hub Cloud
Oracle Analytics Cloud (OAC)
Oracle
VPNaaS
Oracle Object
Storage Cloud
Oracle
NoSQL
Database
Oracle
DataSync
Oracle Cloud Infrastructure
Oracle Data Integrator (ODI)
Golden Gate
O r a c l e B i g D a t a S Q L C l o u d
Executive
VP
LOB Manager
Business Analyst
Data Scientist
Data Engineer
IT
Role
text
Structured Data Semi-structured Data Unstructured Data
devices
logs
sensors
IoTLinkedInFacebook
Google
Analytics
Twitter Social Media thingsEnterprise data
ERP HCMCX
POS
Planning
Transactions
videoaudio

44. 44
Oracle Big Data
Cloud Service
(BDCS)
Data Engineering Services
Oracle Autonomous
Data Warehouse
Cloud Service (ADWC)
Oracle IDCS
Identity &
Access
Management
Oracle Event Hub Cloud
Oracle Analytics Cloud (OAC)
Oracle
VPNaaS
Oracle Object
Storage Cloud
Oracle
NoSQL
Database
Oracle
DataSync
Oracle Cloud Infrastructure
Oracle Data Integrator (ODI)
Golden Gate
O r a c l e B i g D a t a S Q L C l o u d
Executive
VP
LOB Manager
Business Analyst
Data Scientist
Data Engineer
IT
Role
text
Structured Data Semi-structured Data Unstructured Data
devices
logs
sensors
IoTLinkedInFacebook
Google
Analytics
Twitter Social Media thingsEnterprise data
ERP HCMCX
POS
Planning
Transactions
videoaudio

45. 45
Oracle Big Data
Cloud Service
(BDCS)
Data Science Services
Oracle Autonomous
Data Warehouse
Cloud Service (ADWC)
Oracle IDCS
Identity &
Access
Management
Oracle Event Hub Cloud
Oracle Analytics Cloud (OAC)
Oracle
VPNaaS
Oracle Object
Storage Cloud
Oracle
NoSQL
Database
Oracle
DataSync
Oracle Cloud Infrastructure
Oracle Data Integrator (ODI)
Golden Gate
O r a c l e B i g D a t a S Q L C l o u d
Executive
VP
LOB Manager
Business Analyst
Data Scientist
• Ingest & Model
• Transform, ML
• Analyze
Data Engineer
IT
Role
text
Structured Data Semi-structured Data Unstructured Data
devices
logs
sensors
IoTLinkedInFacebook
Google
Analytics
Twitter Social Media thingsEnterprise data
ERP HCMCX
POS
Planning
Transactions
videoaudio

46. 46
Oracle Big Data
Cloud Service
(BDCS)
SQL Querying Service
Oracle Autonomous
Data Warehouse
Cloud Service (ADWC)
Oracle IDCS
Identity &
Access
Management
Oracle Event Hub Cloud
Oracle Analytics Cloud (OAC)
Oracle
VPNaaS
Oracle Object
Storage Cloud
Oracle
NoSQL
Database
Oracle
DataSync
Oracle Cloud Infrastructure
Oracle Data Integrator (ODI)
Golden Gate
Oracle Big Data SQL Cloud
Executive
VP
LOB Manager
Business Analyst
• Analyze
Data Scientist
Data Engineer
IT
Role
text
Structured Data Semi-structured Data Unstructured Data
devices
logs
sensors
IoTLinkedInFacebook
Google
Analytics
Twitter Social Media thingsEnterprise data
ERP HCMCX
POS
Planning
Transactions
videoaudio

47. 47
Oracle Big Data
Cloud Service
(BDCS)
Self-Services for Business Users
Oracle Autonomous
Data Warehouse
Cloud Service (ADWC)
Oracle IDCS
Identity &
Access
Management
Oracle Event Hub Cloud
Oracle Analytics Cloud (OAC)
Oracle
VPNaaS
Oracle Object
Storage Cloud
Oracle
NoSQL
Database
Oracle
DataSync
Oracle Cloud Infrastructure
Oracle Data Integrator (ODI)
Golden Gate
O r a c l e B i g D a t a S Q L C l o u d
Executive
VP
LOB Manager
Business Analyst
• Ingest & Model
• Transform, ML
• Analyze
Data Scientist
Data Engineer
IT
Role
text
Structured Data Semi-structured Data Unstructured Data
devices
logs
sensors
IoTLinkedInFacebook
Google
Analytics
Twitter Social Media thingsEnterprise data
ERP HCMCX
POS
Planning
Transactions
videoaudio

48. Big Data Solution
Implementation Approach

49. 49
Big Data Best Practices
Converge various data engineering/science operations onto a coherent and comprehensive platform.
Doing this improves efficiency and effectiveness of a big data solution.
Choose Cloud for a Big Data Solution
• Avoid the complex installation and configuration of the various Big Data frameworks
• Concentrate instead on the business value
• Stay up to date with continuously evolving open source technologies
• Start small and focused but with scaling out in mind from the start
• Infrastructure elasticity at different independent levels: Cluster scale up/down, in/out; Storage,
Compute (CPU and Memory)
• Pay for processing when needed, as much as needed

50. 50
Big Data Best Practices
Big data is not only a technology solution, but a business driver
• Data accessible to the right people, not just data scientists and IT
• Empower business analysts and end users
• Make data lake readily accessible through a variety of tools (seamless access to HDFS, DB
through web, alerts and mobile voice recognition)
Machine learning is key to success
• Aim at automating data preparation; this allows you to easily scale and be more productive
• Integration of external data with enterprise data in a secure, scalable and reliable manner is
essential to success
• Machine learning is key to success when dealing with big data

51. Oracle Analytics Cloud
Makes the Most of a
Data Lake

52. 52
Steps to Create & Manage a Data Lake with OAC
Discover
• Discover &
Access
Various
Sources
Prepare
• Integrate &
Transform
Analyze
• Interactive
Visualization
Predict
• Machine
Learning &
Modeling

53. 53
OAC for Data Discovery
Step 4
Predict
Step 3
Analyze
Step 2
Prepare
Step 1
Discover
• Leverage OAC
adapters to connect
to a variety of data
sources
• Ingest data into the
data lake
• Use OAC to
replicate data into
Oracle big data or
Oracle DB

54. 54
OAC for Data Discovery
Manage a catalog of data assets
• Projects
• Connections
• Data sets
• Data flows and sequences
Step 4
Predict
Step 3
Analyze
Step 2
Prepare
Step 1
Discover

55. 55
OAC for Data Preparation
Prepare data sets
• Ease of use: Spreadsheet-like transformations
• Remove duplicates, replace nulls and standardize inconsistent values
• Create custom groups and expressions
Step 4
Predict
Step 3
Analyze
Step 2
Prepare
Step 1
Discover

56. 56
OAC for Data Preparation
Create data flows to map to new
data sets
• Intuitive data transformation
flows
• Immediate feedback in data
preview
• Function shipping: Push-down
of execution into sources
• Native execution in Spark for
data lake
• Load data into data sets,
databases or Essbase cubes
Step 4
Predict
Step 3
Analyze
Step 2
Prepare
Step 1
Discover

57. 57
OAC for Data Analysis
Visualize & present
• Automatic chart creation
based on intelligent data
services
• Rich palette of built-in
visualizations
• Single-click trending and
forecasting, clustering
and outliers detection
Step 4
Predict
Step 3
Analyze
Step 2
Prepare
Step 1
Discover

58. 58
OAC for Data Analysis
Support for
custom-built
external
visualization
plugins
Step 4
Predict
Step 3
Analyze
Step 2
Prepare
Step 1
Discover

59. 59
OAC for Data Analysis
Automatic explanation of
data sets
• Explore and
understand
unfamiliar data
• Automatic pattern
detection
• Guide users towards
strongest correlated
factors and
variances from norm
Step 4
Predict
Step 3
Analyze
Step 2
Prepare
Step 1
Discover

60. 60
OAC for Predictions
Advanced transforms and scripts in data flows
• Time series forecast
• Predict possible future trends based on past value patterns
• Based on ARIMA model
• Sentiment snalysis
• Analysis of natural language based on term usage
• Custom scripts in Python and R
Step 4
Predict
Step 3
Analyze
Step 2
Prepare
Step 1
Discover

61. 61
OAC for Predictions
Machine learning data flows
• Use data flows to build machine learning pipelines
• Train and score models through data flows
Variety of ML algorithms
• Numeric prediction
• Multi-classifier
• Binary classifier
• Clustering
• Customer algorithms
Step 4
Predict
Step 3
Analyze
Step 2
Prepare
Step 1
Discover

62. 62
Manage and Monitor
Leverage OAC to schedule and automate data lake activities
• Data replication jobs
• Data set refreshes
• Setup recurring job schedules
• Sequence data flows

63. 63
How to Get Started
• Explore Cloud Services
• Oracle Big Data Cloud
https://cloud.oracle.com/en_US/big-data-cloud
• Oracle Analytics Cloud
https://cloud.oracle.com/en_US/biz-analytics
• Hear from the Experts
• Best practices and approach to innovating using big data
platform
http://blogs.oracle.com/bigdata
• Try a Big Data Guided Trial
• Step by step guide to building a fully functional data lake
http://www.oracle.com/bigdatajourney

64. Questions
Type your question into the chat box

65. 65
Next up:
[Guide] The Future of Big Data: Why Traditional Data
Warehouses Won’t Solve Your Big Data Challenges
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66. Thank You