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Overcoming Challenges
with Distributed Data to
Maximize Business Value
GUEST SPEAKERS
Inessa Gerber, Director of Product Management, Denodo
Colin Dover, Business Technology Platform, Center of Excellence, SAP
TDWI EXPERT PANEL
David Stodder
Senior Director of TDWI Research
for Business Intelligence
Expert Panel Webinar Sponsors
Overcoming Challenges
with Distributed Data to
Maximize Business Value
TDWI Research Perspectives
TDWI EXPERT PANEL
David Stodder
Senior Director of TDWI Research
for Business Intelligence
Distributed Data: Here – and Here to Stay
• Data universe continues to expand: 147 zettabytes
projected to be created in 2024 (Statista)
• Digital transformation of business processes and
applications, smart devices and sensors, online
channels
• Data democratization and self-service: Tendency for
siloed data systems to proliferate
• Users want single, trusted source of truth based on
relevant, complete, and diverse data
• Speed of business demands faster data system
development and deployment
• Analytics, AI/ML, and LLMs/generative AI: Learning
from massive and diverse data to generate insights
• Contextual understanding based on multiple sources
• Data-rich business applications need continuous
data
Image credit: FxTransparency
Copyright © 2024 TDWI
Organizations Need a Strategy for Distributed
Data
• Data silos and fragmentation:
• 38% in TDWI research say silos create significant
challenges for data access, integration, management,
and governance
• 61% problems with data quality, completeness, and
consistency
• Often drives need for considerable data movement
• Data in transition: Cloud migration and hybrid
multicloud environments increase demand for
distributed data strategy
• Top priorities with cloud data in TDWI research:
• Connect to and integrate on-premises and cloud
data
• Enable access to and sharing of data in multiple
cloud data platforms
• Scalability and support for growth in concurrent
users
• Strategy for data silos (due to unplanned cloud
adoption)
• Solving access control, security, and governance
Copyright © 2024 TDWI
User Experience Challenges with Distributed
Data
• Challenges in improving user productivity and the
realization of business value from data
• Not above complexity: Users have to code or are
dependent on IT developers
• Sources and locations can change unexpectedly for
reports, dashboards, and analytics
• Adding new data is often slow, driving users to spin up
their own data systems (and more silos)
• 31% say data integration and management are too
inflexible for changing requirements
• Haphazard user journeys: Users with difference levels
of experience piece together content from multiple
data sources, which can lead to inconsistent quality
and adherence to governance rules
Copyright © 2024 TDWI
Distributed Data Governance and Quality
Challenges
• Data governance: Accountability for rules, policies,
and practices for protecting sensitive data, controlling
access, and aligning with security, masking,
anonymization, etc. practices
• 43% say developing an inventory of data assets is a
major challenge – exacerbated by data silos
• Data lineage: Important to know data origins, ownership,
and how data is being used and shared; also, for AI
explainability
• Local data residence requirements and differing
regulations can restrict data movement
• Data quality: Similar issues
• Improving trust in data quality is a top data
modernization goal for most organizations surveyed by
TDWI
• Poor data quality erodes trust downstream in
dashboards, analytics, and data-driven decisions
Copyright © 2024 TDWI
Data Integration, Transformation, and Pipeline
Challenges
• The labyrinth: Complex data pipelines and ETL
processes
• Delays lead to business insight delays; inability to
develop and test AI/ML
• Data integration and pipeline processes are often
complicated and heavily manual
• Metadata chaos where there is no centralized
metadata management
• Concerns about cost and performance; hard to
allocate resources to the most important workloads
• Data integration strategic priorities in TDWI
research:
• Reduce unnecessary data movement
• Simplify management and ensure consistency
• Enable planned growth and scalability
• Encourage reuse and collaboration
Copyright © 2024 TDWI
Poll Question #1
Which of the following is your biggest challenge in managing distributed data and
providing users with more complete views and access?
Disparate data silos, including hybrid multicloud, thwart complete single views and access
Data governance is incomplete and not holistic across distributed data
Data quality is problematic and inconsistent
Data pipelines, ETL, and connectivity are complex, slow, and too manual
Data management is not efficient and cost-effective
Other (please let us know in the Ask a Question box)
Tech Trends Key to Solving Distributed
Challenges
• Data catalogs and data intelligence
• Enabling sensitive data inventory and tracking
• Centralized information to fix data quality problems
• Data lineage: Catalog for recording
• Integration with MDM, business glossaries, and semantic layers for complete data
intelligence
• AI-infused automation replacing traditionally manual work
• Data fabrics and virtualization
• Architectural layer to reduce friction in connecting to distributed data; single point of
access
• Metadata (data catalog) critical to location, governance
• Data mesh
• People and process focus; domain empowerment for eliminating delays in
development and delivery of data as a product
• Putting the customer of data products front of mind
• Federated and automated governance constraints
• Data silo consolidation
• Using cloud data platforms to reduce silos; unified data warehouse and data lake
Copyright © 2024 TDWI
Poll Question #2
Which of the following strategies are being used by your organization to address
distributed data challenges and improve data management, governance, integration,
and access? (Please select all that apply.)
Data virtualization and/or data fabric
Data mesh
Data consolidation to reduce data silos
Deploying new or expanding current enterprise data catalog
We do not have a distributed data strategy
Other (please let us know in the Ask a Question box)
Thank You
TDWI WEBINAR
David Stodder
Senior Director of TDWI Research
for Business Intelligence
dstodder@tdwi.org
@dbstodder
Expert Panel Discussion
Colin Dover
Business Technology Platform,
Center of Excellence
SAP
David Stodder
Senior Director of Research
Business Intelligence
TDWI
Inessa Gerber
Director of Product Management
Denodo
Audience Q&A with Speakers
TDWI WEBINAR
Speaker Contact Information
Colin Dover
Business Technology Platform,
Center of Excellence
SAP
c.dover@sap.com
David Stodder
Senior Director of Research
Business Intelligence, TDWI
dstodder@tdwi.org
Inessa Gerber
Director of Product Management
Denodo
igerber@denodo.com
Thank You to Our Expert Panel Webinar
Sponsors
Follow Us on Social Media
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tdwi.org/
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tdwi.org/facebo
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Thank You for attending!

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Expert Panel: Overcoming Challenges with Distributed Data to Maximize Business Value

  • 1. Overcoming Challenges with Distributed Data to Maximize Business Value GUEST SPEAKERS Inessa Gerber, Director of Product Management, Denodo Colin Dover, Business Technology Platform, Center of Excellence, SAP TDWI EXPERT PANEL David Stodder Senior Director of TDWI Research for Business Intelligence
  • 3. Overcoming Challenges with Distributed Data to Maximize Business Value TDWI Research Perspectives TDWI EXPERT PANEL David Stodder Senior Director of TDWI Research for Business Intelligence
  • 4. Distributed Data: Here – and Here to Stay • Data universe continues to expand: 147 zettabytes projected to be created in 2024 (Statista) • Digital transformation of business processes and applications, smart devices and sensors, online channels • Data democratization and self-service: Tendency for siloed data systems to proliferate • Users want single, trusted source of truth based on relevant, complete, and diverse data • Speed of business demands faster data system development and deployment • Analytics, AI/ML, and LLMs/generative AI: Learning from massive and diverse data to generate insights • Contextual understanding based on multiple sources • Data-rich business applications need continuous data Image credit: FxTransparency Copyright © 2024 TDWI
  • 5. Organizations Need a Strategy for Distributed Data • Data silos and fragmentation: • 38% in TDWI research say silos create significant challenges for data access, integration, management, and governance • 61% problems with data quality, completeness, and consistency • Often drives need for considerable data movement • Data in transition: Cloud migration and hybrid multicloud environments increase demand for distributed data strategy • Top priorities with cloud data in TDWI research: • Connect to and integrate on-premises and cloud data • Enable access to and sharing of data in multiple cloud data platforms • Scalability and support for growth in concurrent users • Strategy for data silos (due to unplanned cloud adoption) • Solving access control, security, and governance Copyright © 2024 TDWI
  • 6. User Experience Challenges with Distributed Data • Challenges in improving user productivity and the realization of business value from data • Not above complexity: Users have to code or are dependent on IT developers • Sources and locations can change unexpectedly for reports, dashboards, and analytics • Adding new data is often slow, driving users to spin up their own data systems (and more silos) • 31% say data integration and management are too inflexible for changing requirements • Haphazard user journeys: Users with difference levels of experience piece together content from multiple data sources, which can lead to inconsistent quality and adherence to governance rules Copyright © 2024 TDWI
  • 7. Distributed Data Governance and Quality Challenges • Data governance: Accountability for rules, policies, and practices for protecting sensitive data, controlling access, and aligning with security, masking, anonymization, etc. practices • 43% say developing an inventory of data assets is a major challenge – exacerbated by data silos • Data lineage: Important to know data origins, ownership, and how data is being used and shared; also, for AI explainability • Local data residence requirements and differing regulations can restrict data movement • Data quality: Similar issues • Improving trust in data quality is a top data modernization goal for most organizations surveyed by TDWI • Poor data quality erodes trust downstream in dashboards, analytics, and data-driven decisions Copyright © 2024 TDWI
  • 8. Data Integration, Transformation, and Pipeline Challenges • The labyrinth: Complex data pipelines and ETL processes • Delays lead to business insight delays; inability to develop and test AI/ML • Data integration and pipeline processes are often complicated and heavily manual • Metadata chaos where there is no centralized metadata management • Concerns about cost and performance; hard to allocate resources to the most important workloads • Data integration strategic priorities in TDWI research: • Reduce unnecessary data movement • Simplify management and ensure consistency • Enable planned growth and scalability • Encourage reuse and collaboration Copyright © 2024 TDWI
  • 9. Poll Question #1 Which of the following is your biggest challenge in managing distributed data and providing users with more complete views and access? Disparate data silos, including hybrid multicloud, thwart complete single views and access Data governance is incomplete and not holistic across distributed data Data quality is problematic and inconsistent Data pipelines, ETL, and connectivity are complex, slow, and too manual Data management is not efficient and cost-effective Other (please let us know in the Ask a Question box)
  • 10. Tech Trends Key to Solving Distributed Challenges • Data catalogs and data intelligence • Enabling sensitive data inventory and tracking • Centralized information to fix data quality problems • Data lineage: Catalog for recording • Integration with MDM, business glossaries, and semantic layers for complete data intelligence • AI-infused automation replacing traditionally manual work • Data fabrics and virtualization • Architectural layer to reduce friction in connecting to distributed data; single point of access • Metadata (data catalog) critical to location, governance • Data mesh • People and process focus; domain empowerment for eliminating delays in development and delivery of data as a product • Putting the customer of data products front of mind • Federated and automated governance constraints • Data silo consolidation • Using cloud data platforms to reduce silos; unified data warehouse and data lake Copyright © 2024 TDWI
  • 11. Poll Question #2 Which of the following strategies are being used by your organization to address distributed data challenges and improve data management, governance, integration, and access? (Please select all that apply.) Data virtualization and/or data fabric Data mesh Data consolidation to reduce data silos Deploying new or expanding current enterprise data catalog We do not have a distributed data strategy Other (please let us know in the Ask a Question box)
  • 12. Thank You TDWI WEBINAR David Stodder Senior Director of TDWI Research for Business Intelligence dstodder@tdwi.org @dbstodder
  • 13. Expert Panel Discussion Colin Dover Business Technology Platform, Center of Excellence SAP David Stodder Senior Director of Research Business Intelligence TDWI Inessa Gerber Director of Product Management Denodo
  • 14. Audience Q&A with Speakers TDWI WEBINAR
  • 15. Speaker Contact Information Colin Dover Business Technology Platform, Center of Excellence SAP c.dover@sap.com David Stodder Senior Director of Research Business Intelligence, TDWI dstodder@tdwi.org Inessa Gerber Director of Product Management Denodo igerber@denodo.com
  • 16. Thank You to Our Expert Panel Webinar Sponsors
  • 17. Follow Us on Social Media tdwi.org/linkedi n tdwi.org/ x tdwi.org/facebo ok tdwi.org/youtub e
  • 18. Thank You for attending!