Data in Motion to Accelerate Your Mission
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Government Data Movement Challenges
Data Lifecycle: Impacts and Opportunities
The Role of Analytics & Emerging Technologies
Zero Trust Takes Center Stage
Delivering Data Security & Governance
Real-World Public Sector Use Cases
Resources
Government Data Management Challenges
The future of public sector missions depends directly on a cohesive data management platform and strategy. Government agencies at all levels – federal, state, and local – face challenges with data collection, integrating new data sources, and leveraging data to gain insights. According to a report quoted by Nextgov, 72 percent of agency respondents say they don’t have “full knowledge of where their data is stored.” And only 33 percent reported they could “fully classify their data.” There’s a massive data opportunity for governments, but governments today struggle with scattered, siloed, and inaccessible data.
contents
CHAPTER 1
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of government agencies don’t have full knowledge of where their data is stored
say they can fully classify their data
72
33
%
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Data is constantly growing and constantly in motion, generated by a wide range of sources. As a result, government IT leaders and teams must scale multiple hurdles to unlock the value of their data. These challenges include:
CTA
In a word: Everyone.
Quantity & complexity of data sources
Data flow observability & control
Data integrity
Security & governance
Data moves through difficult environments
Collection of data from the edge to the data center
Data pipeline maintenance
Who’s Using Data?
• IT • Data Teams • DevOps Teams • Business Analysts • Marketing • Accounting/Finance • Product Management • C-Level
Anyone and everyone whose job intersects data – from the CIO to data scientists to non-technical subject matter experts who lead business solutions – need the ability to build, manage, deliver and gain insight from data flows.
Data in motion is the foundation of effective data management and an end-to-end data lifecycle that empowers the most ambitious public sector missions. Agencies across federal, state, and local governments must be able to collect, ingest, and move data to where it can be best analyzed, reported, and used to deliver new insights and predict future ones.
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CHAPTER 3
Harnessing data in motion, government IT leaders can turn yesterday’s data challenges into tomorrow’s agency-defining opportunities. Data in motion enables better, faster decision-making, increased transparency, reduced waste, and a wealth of other benefits. To get there, you must be able to take data from where it is and move it to where it can best be used – for anything, by anyone.
This is the guiding principle of Cloudera DataFlow, a data-in-motion platform that supports the entire streaming data journey, from collection and flow management at the edge to stream processing and analytics – and everything in between. And embedded low-code technology empowers users no matter their individual role: Users focus on business logic, while the platform abstracts away much of the backend complexity.
The Role of Analytics and Emerging Technologies
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CHAPTER 2
Analytics
Unaddressed data management challenges create a cascading series of subsequent issues, not just in terms of operational complexity but also in opportunities lost. Without a sound data platform and strategy – one capable of ingesting and processing high volumes of data in real time – agencies are unable to analyze streaming data for real-time insights that can improve decision-making. Cloudera DataFlow (CDF) is an end-to-end platform that ingests, curates, and analyzes streaming data for key insights and immediate actionable intelligence.
Emerging Tech
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Cloudera Machine Learning for Cloudera Data Platform ensures that data in motion facilitates these fundamental AI/ML needs, ensuring that the right data flows to where it’s needed and that models can be properly managed for drift and other issues.
CDF helps government agencies democratize real-time streaming analytics, improving detection and response to critical events that deliver mission-critical outcomes. As IoT and other streaming sources proliferate, unbounded data streams and events are constantly flowing into the organization. CDF’s stream-processing capabilities help analyze them in real time, identify key event patterns, and escalate key alerts based on predictive insights and actionable intelligence.
As the public sector looks to AI and ML to enhance and expand their missions with predictive insights, they run into similar challenges as the private sector: getting the right data – or enough of it – fed to their models, and then managing and optimizing multiple models in production in a manner that maximizes value and minimizes risk.
Security and governance are critical requirements for any government agency. There’s now a growing need to apply strong cyber security and governance in data streaming, including the implementation of a zero trust strategy in accordance with the January 26, 2022 OMB mandate “requiring agencies to meet specific cybersecurity standards and objectives by the end of Fiscal Year (FY) 2024 in order to reinforce the Government’s defenses against increasingly sophisticated and persistent threat campaigns.” This creates added complexity for IT leaders and teams, especially as the scope and scale of their data grow. Few agencies can throw unlimited resources at the challenge, underscoring the necessity of a low-code-enabled data platform that scales seamlessly and securely across private cloud and on-premises environments.
Delivering Data Security and Governance
Cloudera’s end-to-end approach to data in motion supports a robust data governance model, which must include the entire lifecycle, from data architecture to quality assurance. One data governance framework, shared via CIO.com, covers 10 distinct areas where agencies should establish systematic and formal control (see below).
With CDF and Shared Data Experience (SDX), Cloudera’s Data in Motion philosophy supports the entire streaming data journey from data capture and flow management at the edge; to provisioning that data directly to/from your Kafka messaging backbone; and/or stream processing and analytics. SDX provides a common set of integrated services, including unified security and governance across data centers and cloud environments – increasing consistency and decreasing the existing operational overhead.
Data Governance
Data architecture
Data modeling & design
Data storage & operations
Data security
Data integration & interoperability
Documents & content
Reference & master data
Data warehousing & business intelligence (BI)
Metadata
Data quality
Public Sector Use Cases
Data warehousing & business intelligence
Data Architecture
Data Modeling & Design
Data Storage & Operations
Data Security
Data Integration & Interoperability
Documents & Content
Reference & Master Data
Data Warehousing & Business Intelligence
Data Quality
Next use case
A federal civilian agency was hit with a zero-day exploit, for example, but it was unable to determine the origins of the attack – or detect current or future attacks in a timely manner – using their existing SIEM. As a result, the agency turned to Cloudera DataFlow to strengthen its cyber posture with another significant layer beyond its SIEM, generating significant improvements:
With Cloudera, agencies can bolster their SIEM software and overall cyber readiness by ensuring they have the appropriate visibility and analytics into all of their data – which can be a challenge with SIEM alone.
Enhancing SIEM and Cyber
As computing environments and data become more distributed, so too do the security risks. As organizations are turning toward tools such as Security Information Event Management (SIEM) software to identify risks and breaches. SIEM alone isn’t enough.
The agency now has continuous queries to alert for attacks.
It enabled continuous monitoring of critical systems to help prevent future attacks.
It completed this high-impact, low-cost solution in approximately one month with Cloudera Professional Services.
UCSD built a real-time data logistics platform – deployed in the cloud and using Cloudera DataFlow – that integrates its many data sources with more than 180 integrations and securely moves data in real-time to where it’s needed. In addition to massive improvements to end user experience, UCSD cut the time required for data analytics and integration projects from 10 weeks to less than two.
Supporting Data in Higher Education & Research
Considered one of the top research universities worldwide, the University of California, San Diego (UCSD), recognized that its mission depended directly on modernizing its legacy IT infrastructure and processes.
Recently, Cloudera joined forces with NVIDIA to develop a new capability to accelerate Artificial Intelligence and Machine Learning operations. The IRS became the first customer to utilize the combined technology built on Cloudera Data Platform (CDP).
Combatting & Preventing Fraud
The Internal Revenue Service (IRS) was on a mission to better identify fraud and abuse. The agency’s trove of data created a significant obstacle factoring in both time and cost. Failure to address this challenge meant major implications that would erode credibility and citizen trust.
Through use of this innovative joint Cloudera/NVIDIA capability on CDP, and combined with CDF’s ability to aid in rapid delivery of data, the IRS has improved the speed of data analysis by 10x, while dramatically cutting infrastructure costs by 50%. The result: Work that took up to ten days can now be completed in just a day. The IRS has reduced fraudulent activity and realized efficiency savings ultimately benefiting taxpayers.
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Government needs a sound data strategy to make the most of cloud
whitepaper
Data in Motion to accelerate your mission
Datasheet
Data-in-Motion Philosophy
Solution brief
The Rise of Smart Cities
How State and Local Governments Can Benefit from Data in Motion
Blogs
Accelerate Agency Missions with Data in Motion
Cloudera Addresses Executive Order on Improving U.S. Cybersecurity with Data Analytics
Hybrid Data Cloud Success for State and Local Governments
Winning With Data in the Fight Against Fraud, Waste, and Abuse
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Question: As a percentage of global annual revenue, what was your organization’s most recent profit growth?
Total
Enterprise data strategy has been in place for longer than a year
Enterprise data strategy has been in place for less than a year
No enterprise data strategy in place but plan to within the next 12 months
Average profit growth
4.85%
5.97%
4.17%
2.50%
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96%
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Success Story: Western Union
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