Raise your hand if you’ve ever had a line of business user go rogue and create a dataset without telling you. Don’t be shy… You’re in good company. In a recent survey of over 650 data decision-makers and practitioners, 68% said it had happened to them too.
And as frustrating as it may be, it shouldn’t come as a surprise. I don’t know who data’s PR person is, but they’ve been in overdrive for years now. Everyone knows that using data in decision-making drives better outcomes.
As a result, line of business users have become increasingly savvy about the data tools they can employ to drive value and are not afraid to use them. Gartner analysts estimate that by 2025, more than 50% of enterprise-critical data will be created and processed outside the data center or cloud. Unfortunately, this means even data integrations will be created outside of IT’s purview, leading to new data siloes.
When you add that to the diversity of modern infrastructures that span on-premises and multiple clouds, you end up with a seriously fragmented data supply chain that’s hard to understand, govern, and manage.
57% of over 650 data leaders and practitioners say fragmentation in the data supply chain has made it hard to understand, govern, and manage data in their organization.
The sheer complexity of connecting the varied data sources and ensuring consistency of definitions makes deployments and subsequent updates arduous. It’s challenging to enforce consistent security measures to protect data as it flows between on-premises, cloud, and edge sources. And regulatory requirements that restrict access to certain data can be inadvertently violated by users who are not compliance experts.
The more apps, systems, data sources, and tools that get added to the ecosystem, the harder it becomes to maintain visibility and control. Organizations risk reputational damage, regulatory fines, and security breaches without clear visibility of what data pipelines are in place and how and where data is being used.
Over 40% of survey respondents were unable to enforce consistent security measures to protect data — nearly the same amount who were unable to maintain governance and automate policy controls around data.
The good news is, there is a better way.
Enable Innovation, Prototyping, and Experimentation With Centralized Guardrails
StreamSets platform helps you take control of the data “wild west” and simultaneously empower your line of business users in three ways.
- Bridge the gap between new and legacy environments easily and securely. A data “mission control” for secure (i.e., without punching through firewalls) deployment of data processing components in any environment lets you easily move between clouds and on-premises environments. You’ll extract maximum value from your data faster while lowering the cost and effort of managing your disparate toolchains.
- See how systems are connected and data is flowing across the enterprise. Topologies give you visibility into data connections and flow across a hybrid landscape, including volume, throughput, and exactly what data is moving between components. Automatically see the creation of new integration points if there is a more direct route for the data, and understand where data comes from to help explain outcomes, for example, in AI/ML models. You’ll reduce operational gaps and increase data transparency, governance, and control.
- Expose hidden problems in your data flows with data SLAs and rules. Create guardrails and quality checks, and then manage by exception. Set up auto-notifications for problems throughout data pipelines related to data quality, sizing, throughput performance, error rates, private/sensitive information leakage, and more with alerts via email, Slack, or other system messages. You’ll address performance, data leakage, quality, and other risks before they affect the business.
And keep your eyes open for our exclusive research report on taking control of the data “wild west” while empowering the LOB — coming soon!
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