Tamr Achieves Premier Technology Partner Status With SnowflakeLearn More

4 Takeaways from Enterprise Data World

Abstract connections of lines and spheres.

I recently attended Enterprise Data World in Boston, Massachusetts — an educational conference focused on challenges and solutions associated with Data Management. It was a busy show with a lot of enthusiastic sessions and attendees, and some great takeaways.

Overall, some important observations that were made about the state of the industry based on the sessions included:

1) Technology decisions need to fall back on a business driver. This is so important that companies should not even consider an initiative that does not tie to a business driver. When it comes to data, it’s critical to align your data strategy with business strategy. By doing so, you can realize benefits such as improved data quality means, for example, richer customer insights (better customer engagement and retention), clear priorities (better marketing ROI), and a clear picture of cause and effect across all departments.  

2) Technology projects should be assessed from multiple angles to determine the enterprise’s readiness. Too often, directives may come from the top-down, but the global team or the stakeholders may not be ready for such a major cultural shift. That’s why it’s important to start small to introduce new concepts instead of doing a rip and replace. It’s also important to remember that no one tech stack is going to be successful on its own. Instead, it takes incremental evaluation and tactical implementation.

3) Machine Learning is here to stay. Machine learning holds tremendous benefits for data management, as it automates tasks that otherwise are very time-consuming (and not very productive) for data scientists. Solutions that unify datasets as they come in with heavy assistance from machine learning algorithms and continuous learning integration software provide broader access to the enterprise-wide data asset. This results in faster, more consistent, and scalable analytics. One challenge that I heard over the course of the conference regarding machine learning adoption, however, is poor data quality.

4) Customer 360 is critical for all organizations. Short for “a 360-degree customer view”, Customer 360 is a pillar of most data initiatives and should be a goal for every large organization. With the explosive growth of data in cloud computing and CRM systems, organizations of all sizes need to establish a Customer 360 strategy to deliver a compelling customer experience. Customer 360 positions you for success by putting you in sync with your customers and their current and future needs. Your sales and customer service folks want to be competent in front of a customer—there’s nothing more frustrating for the customer or the representative than a disconnect between your organization’s data and the real world.

These are all trends and challenges that we’ve heard from our customers here at Tamr — and they are challenges that we’re working hard to address. To learn more about how Tamr can help address your enterprise’s data management challenges, contact us or schedule a demo.