Tamr + Google Cloud Platform: What’s It Mean?

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Tamr today has announced a collaboration with Google Cloud Platform to deliver our scalable data preparation system on Google Cloud Platform via Google Cloud Dataflow.

So Tamr’s in the cloud.

But what’s it mean for customers?

With Tamr and Google Cloud Dataflow, the full volume and variety of a customer’s data can be prepared and published for analysis much more simply, quickly and efficiently. Companies can now unify and clean data from many diverse sources without investing in expensive data integration expertise or infrastructure. And their business analysts can build and publish data sets across the enterprise with limited IT support and coding required. The result is streamlined collaboration between IT and the business users they support, with both groups able to move faster and get more done.

Here’s an example:

Suppose you’re a regional sales and marketing analyst at a global manufacturer with divisions, distributors and dealers arrayed across national and local levels. Each group has its own sales and marketing systems and customer outreach processes — often resulting in such inefficiencies as multiple divisions contacting customers on the same topic and missed cross-selling opportunities.

Looking to coordinate and optimize sales and marketing at the regional level, you naturally seek a unified,  360-degree customer view. But data is fragmented across diverse division-specific Order Management CRM and even spreadsheet systems. These in turn need to be integrated with corporate data (from web traffic and other sales/marketing touch points) and even external sources (e.g., demographic data, credit data, etc.). Integration projects to date have been largely manual, but this has proved to be an expensive and time-consuming process that has left IT with a significant backlog and analysts waiting too long to respond to business needs.

The combination of Tamr and Google Cloud Dataflow was designed exactly for your sort of challenge: a flexible and powerful way for analysts to find, gather, unify and format data from many disparate sources … all in a cloud setting with limited coding required by end users or much direct support by IT.

Discovery: With Tamr’s data unification system, you can pull raw data from hundreds or thousands of sources, whether it’s stored in corporate, one of your regions or in the cloud (such as Salesforce or social media). To find the specific data you need, you use a simple keyword search, with Tamr returning matching data sets, attributes and shared projects.

Quality: Invariably, this data is dirty and disorderly, reflecting its disparate sources and schemas. Tamr’s machine-driven, human-guided system resolves quality problems without requiring you to know everything about the source data. Tamr’s algorithms remedy the problems they can, then generate questions for data experts, aggregate their responses, and feed them back into the system. You can also take advantage of existing transformations to clean the data so you don’t have do it yourself.

Unification and Enrichment: Tamr uses “fuzzy” joins and aggregation to enrich your data. For example, the system unifies Customer data with Transactional data by matching attributes and records from hundreds of disparate sources, allowing you to roll up the results into something so valuable as “monthly revenue per customer across the region.” Tamr accomplishes this through machine learning combined with expert input from business users, which means less work for IT. Unification projects are also reusable, so business users can leverage each other’s work and avoid overloading IT with redundant one-off requests.

Preview and Publish: Tamr’s WYSIWYG interface lets you preview transformations interactively and, once satisfied, publish the complete data set to Google BigQuery or Excel (so that other analysts could potentially expand on it). For BigQuery, Tamr converts your preview into a Cloud Dataflow job that will apply your changes to the whole data set — then move it to BigQuery. With a push of a button, the job executes, making management of this process easier than ever. By using Google Cloud Dataflow to publish the resulting datasets, you’ll be able to move and transform even massive datasets efficiently — radically improving the scale and speed of deployment.

The result of this fast, easy process? A clean, unified view of your data that puts the customer at the center of all your activities moving forward – whether it’s eliminating duplicative contacts or delivering the right upsell offers at exactly the right time.

For more information about Tamr with Google Cloud Dataflow, including a free preview of the solution, click here.