Get fresh updates from Hortonworks by email

Once a month, receive latest insights, trends, analytics information and knowledge of Big Data.


Sign up for the Developers Newsletter

Once a month, receive latest insights, trends, analytics information and knowledge of Big Data.


Get Started


Ready to Get Started?

Download sandbox

How can we help you?

* I understand I can unsubscribe at any time. I also acknowledge the additional information found in Hortonworks Privacy Policy.
closeClose button
prev slide
How Big Data in Aviation Is Transforming the Industry
March 21, 2018
Three Speakers You Don't Want to Miss at DataWorks Summit Berlin 2018
Next slide

How Advanced Is Your Data Management System?

How advanced is your data management system? How do you measure that? Where does your system sit on the maturity scale? One way to answer these questions by gauging how easily you can onboard a new project or data stream inside your enterprise, and how quickly and securely users can access the data they need.

Where Do You Stand Today?

Start by measuring the time it takes for new data projects to move from inception to pilot to production. This offers a good estimate of the capacity of the data programs within your organization. If you roll out new initiatives in a programmatic manner, and your governance policies and processes can onboard any new data source, then your system is on the mature side.

Then assess how long it takes between the moment end users state a need for certain data and when they ultimately have access to it. Also determine how much IT involvement is required to fulfill these requests. In a data-optimized organization, business users will access data through self-service, and policies and processes will already be in place to ensure the data’s security and governance. Conversely, if your process is taking months, includes high IT-team involvement, and you have no guarantees of security or governance, then your organization is low on the maturity scale.

If those questions revealed some inadequacy in your business’s data management system and governance, you’re not alone. The “2017 Global Data Management Benchmark Report” by Experian found that 51 percent of organizations believe their current data governance programs are ineffective. As data management continues to evolve, organizations must get better at both governing and managing their data. Your company must have the right systems in place—people, processes, and technology—to manage data effectively.

Where Do Organizations Go Wrong With Data Management and Governance?

When a sales or marketing team is the evangelist for big data initiatives inside an organization, they often work only within the limits of their silo. The team frequently fails to plan for other business units that may want to build on its success, and it doesn’t consider the data architecture that would support scale and agility. In addition, it overlooks the opportunity to set up governance policies that can apply locally and globally. This failure to plan can often stop success in its tracks. That one business unit may achieve some big data wins, but those won’t translate to wins for other departments.

This failure also typically points to a CEO who won’t champion the strategy. While businesses need data champions, such as a chief information officer (CIO) or chief data officer (CDO), the CEO needs to embrace the role of a visionary. The commitment to being a data-driven organization comes from the top down. This needs to be reflected in both business strategy and operations with consistent support from the C-suite.

Even with the right architecture in place and the support of the CEO, some businesses fail to accurately estimate the effort and skill that a big data journey entails. The data skills of your team will determine how far and how fast your business can take its data transformation. Part of your business strategy should be to continually add new capabilities to your team.

What Does an Effective Global Data Management System Look Like?

Effective global data management takes into account the reality of today’s and tomorrow’s data architectures. Few organizations have a single data lake governed by a single data architecture inside a single tier. Most businesses face data sprawl as a result of the proliferation of data sources and types that are located on various architectures and spread over a variety of tiers on premises, in the cloud, or a hybrid of both. An advanced data management system allows a business to secure, access, govern, and consume data regardless of its type or location.

To achieve this ideal, you need open source architectures won’t leave you constrained by reliance on a single vendor or hindered when technology changes occur. To match the volume of data creation, you’ll also need a system that is scalable and can match the changeable nature of your business demands. The European Union (EU)’s General Data Protection Regulation (GDPR) may be the first widespread data governance challenge, but it won’t be the last. You’ll need an agile global data management solution that defines and enforces data and governance security policies seamlessly.

How effective is your global data management system? Watch this recorded webinar to learn more about global data management in a multi-cloud hybrid world.

Leave a Reply

Your email address will not be published. Required fields are marked *