Data consumers from business analysts to data scientists often find it takes weeks, months or longer to access data products with commercially or personally sensitive information. The reason isn’t unwillingness to share or any lack of technology to move the data to users and applications. What stands in the way is a mountain of questions, decisions and actions needed to approve and protect data access, and a lack of tools to automate that workstream. This is data’s last mile problem.

The “last mile” is the final leg of any supply chain when products leave a central hub and make their way to unique destinations. The stage with the shortest distance consumes the most time and cost because each last mile is unique and must be handled differently.

In data management, the technology is there to move huge volumes of data from operational systems to data lakes and warehouses and on to analytics and BI tools shared by thousands of users. The seamless process hits obstacles in the last mile because individual projects need approval plus security and privacy measures that fit their unique context.

Is this scenario familiar?

1. A business user wants to verify a key business decision with customer data they can see in their data catalog. They ask their manager for access.
2. The manager learns their department doesn’t have prior approval to access that source and must contact the governance team.
3. The governance team asks a long series of questions about the project, with days, nights, weekends and holidays in-between.
4. Eventually, they refer the case to the legal team, who determines that regulations apply to this use of data and returns a set of conditions that must be met.
5. The governance team translates those conditions into specific row filtering and column masking requirements the data needs to meet.
6. The data team engages data engineers to write custom code that addresses the compliance requirements.
7. Finally, a data architect builds the data flow that provisions redacted data to a tired, confused and world-weary business user.

It’s a painfully slow and tedious process, only for the user to find out the dataset has quality issues, and the process has to start again in emails, phone calls, support tickets, instant messages and video conferences that are impossible to audit. (See Figure 1.)

Fig. 1. Access to data — especially sensitive data — is a complex process in many organizations.

Good decisions are highly prized, but the manual steps to reach data hamper timely insights. In some cases, it takes so long to access data that the results are stale and ineffective.

Many enterprises made savvy and appropriate investments:

• They deployed systems to collect, store, manage, aggregate and analyze data.
• They discovered, classified, cataloged and curated data from every source.
• They designed data shopping experiences for analysts and business users.

Yet many data-driven initiatives still stall or falter in the last mile, and some never reach completion.

Yet, the time it takes to get approved and protected data in front of users is pushing projects, goals and strategies off track.

• Complex, manual, and inconsistent approval processes delay access to data.
• Legacy governance measures restrict access for many users and leave useful data assets untapped.
• Written policies say how data should be used, but don’t make sensitive data safe for use.

Regulatory oversight, compliance mandates, consumer attitudes, corporate policy and risk appetite are all factors that affect how data is handled in the last mile. Decision-makers in groups like governance, legal and compliance often seem at odds about how to proceed safely. Data consumers lose the appetite to follow the prescribed process, which only pushes them down riskier routes.
 

Organizations can solve their last mile problems with intelligent data access management capabilities that automatically enforce controls across their entire data supply chain, including:

• Policies that apply automatically across complex data ecosystems.
• A comprehensive range of controls to protect data, such as access controls, data protection techniques and event logging.
• Policy authoring that uses conditional logic to scale across multiple use cases.
• Policy authoring that uses metadata from a data catalog to ensure the applied controls are fit for each use case.
• Consistent, repeatable approval processes managed in a data marketplace.
• A single solution where all stakeholders collaborate.

Informatica’s Cloud Data Access Management, a service of the Intelligent Data Management Cloud™ (IDMC), leverages intelligent discovery, classification and cataloging capabilities to apply controls in a wide range of contexts. Automated policies align data protection to business use and give you speed and scale while avoiding the friction of a multi-party solution.

How does the scenario improve with IDMC?

1. The business user (data consumer) finds the data they want with the intuitive data shopping interface in Informatica’s Cloud Data Marketplace. They place an order, describing their use case.
2. Their request is routed to a user in the governance team (data steward) who can review quickly because information about the project is transparent and immediately available.
3. Access is approved and appropriate policies are applied automatically. Protected data is available for the business user’s preferred tool.

With data products, data access policies and delivery methods already configured, business users get data without friction or delay. There’s no need to engage managers, engineers or architects, and a process that once took weeks or months can be completed in minutes. (See Figure 2.)

Fig. 2. Policy automation and collaborative approval in a data marketplace radically simplify and accelerate access to data.

Informatica can help your organization address data’s last mile problem, making data that’s secure, approved, appropriate and timely for use, plus available to the tools and systems where business users and analysts turn data into value.

Read our full eBook, Deliver A Data Governance Strategy That Gets Data Through the Last Mile, to explore how IDMC empowers your organization to help solve data’s last mile problem.