DataOps aims to align people, processes, and technology to enable more agile data management in support of business goals. It addresses challenges such as slow analytic velocity due to data engineering difficulties and new data governance demands. Hitachi Vantara's DataOps approach promises to deliver the right data to the right people at the right time through components like data engineering, integration, security, quality control, and monitoring processes. It leverages solutions like Pentaho for data integration and Hitachi Content Platform for data storage and management.

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Big Data Expo
18-19 August 2019, Utrecht
DataOps,
the next big wave
Leo Cardinaals
Team Lead Northern and Central EMEA
Digital Insights Solution Engineering

2. © Hitachi Vantara Corporation 2019. All Rights Reserved.© Hitachi Vantara Corporation 2019. All Rights Reserved.
• The alignment of people, process, and technology to enable more agile
and automated approaches to enterprise data management in service of
business goals
DataOps
- Matt Aslett, vice president, data, AI and analytics, 451 Research
• In short: the right information to the right place at the right time to the
right person.

3. © Hitachi Vantara Corporation 2019. All Rights Reserved.© Hitachi Vantara Corporation 2019. All Rights Reserved.
• Analytic velocity is slowed by data engineering challenges that make it
time-consuming to discover, blend, and deliver the data required
• Data governance and compliance requirements place new demands on
what data can be shared and how it should be managed
• Distributed edge-to-cloud infrastructures mean that data is more
distributed than ever before, which introduces a new set of operational
data management challenges
• All leading to not achieving the promise of analytics, machine learning,
and AI to transform operations and drive innovation
DataOps challenges

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1. Your business can scale, which enables the whole organization to get
value from data that matters to them.
2. Data can be governed while it’s being used, reducing your risk and
enabling new capabilities.
3. People can focus on where they are most valuable to the organization
and, as they evolve, the practice will be ready for them.
4. Your company can become a data-first organization — where data
consumers and data creators collaborate easily to drive value across
the enterprise.
Hitachi Vantara DataOps Advantage Promise

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• The right data
‒ To be data agnostic and able to handle all data
• The right place
‒ Wherever this data and you resides
• At the right time
‒ Get the info whenever you need it
How we are going to do this?

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DataOps Model: Five Key Components
Data
Engineering
Integration /
Orchestration
Security /
Privacy
Quality /
Governance
Process
Monitoring

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DataOps Technical Architecture
Data Lake
Source Integration & Standardisation
Aggregation &
Calculation
Data Access & Delivery
Data Access & Delivery
EPM Measures
Financial
KPIs
Non-Financial
KPIs
Analytics
Data Exploration
Data Analytics
Advanced Analytics
Reporting
Standard
Reporting
Adhoc
Reporting
Reporting
Packs
GPM Pack
Exco Pack
Security Authentication
Data Security &
Privacy
Access /
Authorization
Data Archival
Workflow Management
Audit, Balance &
Controls
Model
Management
Technology
Governance
Adjustments
Data GovernanceData Quality
Metadata
Management
Hierarchy
Management
Master & Ref
Data Mgmt
Local Data
Sources
Ingestion
LANDINGZONE(RAWDATA&CTRLREPORT)
File
Data
Txn
US Clearview
UK
FR
DE
CA
MX
FTP Train
FinMIS
Feed to
MI Actual
Feed to
MI Actual
Feed to
MI Actual
UPD
Transformation
Data
Harmonisation
Data Mapping &
Transformation
Data Validation &
Quality
UPD Interface
Batch Analytics
In-Memory
Analytics
Global MI
Actuals
Income
Stmt
Bal Sheet
- Period
Adjustments
Bal Sheet
- Avg
Statistical
Codes
GOLDENSOURCEFORGLOBALREPORTING
INFORMATION
LAYER
Structured
Data Model
Base Tables
Fact Tables
Journal Entry
HIVE
H Catalogue
Map Reduce
H D F S
Customer
behaviour
Real time data
Consolidated
data across
units
MI Reporting
Aggregation
FX Currency
Translation
Overheads
Allocation
Adjustments
Calculations
Aggregations

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• On-premise
• In the Cloud
• Or hybrid
Anywhere
Multi-cloud
Edge Data Center
DataPlane
PDI Con
PDI Con
Data Flow
Blob
S3 GCS
PDI Con PDI Con
PDI Con
ControlPlane
Intelligent Data Operations
Data Flow Monitor Manage
Placement
Advisor
Discover Prepare
Govern
Return on
Data
Status Control
HCP
AW
Edge
AW
Edge
HCP
HCP
HCPHCP

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• Our strategy is laser-focused on providing the data management
infrastructure, metadata-driven data management tools, and policy-
based automation that organizations need to improve data agility
through DataOps
‒ Hitachi Pentaho (Data Integration)
‒ Hitachi Content Intelligence
‒ Hitachi Content Platform
‒ Hitachi Data Lake (future)
‒ Hitachi Data Catalog (future)
‒ Hitachi Edge (future)
Our solutions

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• DataOps is still a relatively new approach, and first steps often start with
improving data pipelines for the purposes of analytics and ML
• Pentaho 8.1 (GA April 2018)
‒ Enable data scientists
‒ Working across ecosystems
• Pentaho 8.2 (GA Nov 2018)
‒ Enable data engineers to work with data scientists
• Pentaho 8.3 (GA Jun 2019)
‒ Deepening data integration across ecosystems
‒ Lay foundation for next generation deployment to streamline data ops
Focus on Pentaho

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• Minimize risk and optimize costs by working across cloud vendors
‒ Google Cloud Storage and BigQuery, Enhanced Amazon S3 and EMR
Pentaho 8.1
• Solve more business problems using an even wider variety of data
‒ Stream ingestion: MQTT, JMS and IBM MQ
‒ Stream and Time Series Visualizations
• Better platform performance and user productivity
‒ Data Lineage improvements

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• Enable data engineers to work with data scientists
‒ Python to deploy Tensorflow, Kersas, models
‒ Jupyter notebook integration
Pentaho 8.2
• Data pipelining
‒ Advanced Message Queuing Protocol (AMQP)
‒ Hitachi Content Platform support
• Improve team productivity and platform scalability
‒ Adaptive Execution Layer support for Metadata Injection

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• Deepening data integration across ecosystems
‒ Kinesis streaming, Redshift bulk load and Snowflake connectivity (multi-cloud)
‒ SAP ECC, SAP BW, SAP ODS connectivity
Pentaho 8.3
• Lay foundation for next generation deployment to streamline data ops
‒ Pentaho Data Integration Container,
Worker Nodes (beta)
• Improve platform usability, quality, and completeness
‒ Data visibility for governance - metadata management with Hitachi Content
Platform, IBM Information Governance Catalog (ICG) integration
‒ Streaming Data Lineage tracking

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So alignment of people,
process, and technology.
Let’s see!

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Questions?

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Thank You

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