Data Unification vs. Data Prep: Why Should You Care?

How does your organization get data into the hands of the analysts who can extract value from it? Self-service data preparation tools had seen a surge in adoption in the past few years as a complement to the data visualization technologies that are are by now widespread in most enterprises. Their popularity has been driven by the empowerment that they bring to line-of-business users who historically were dependent on IT or stuck with underpowered tools like Excel when it came to data preparation. But all tools have their limits.

A new wave of analytic value can come from uniting dozens or even hundreds of enterprise data sets. However, the magnitude of these challenges is beyond the scope of self-service data preparation tools. And the cost and complexity of traditional ETL approaches to many large scale data unification challenges renders them infeasible. Otherwise they would have done the job years ago.

Toph Whitmore, Principal Analyst at Blue Hill Research recently published a report titled Connected Data Delivery: Combining Data Unification and Data Preparation. In it, he distinguishes these two related concepts and shows how they are complementary components of a big data value chain. He illustrates this model with real-world case studies where Tamr customers are using our platform for a new class of large scale data unification projects, and then handing off clean, mastered data sets to business users for ‘last mile’ data prep and analytics.

How does your organization get data into the hands of the analysts who can extract value from it? Self-service data preparation tools had seen a surge in adoption in the past few years as a complement to the data visualization technologies that are are by now widespread in most enterprises. Their popularity has been driven by the empowerment that they bring to line-of-business users who historically were dependent on IT or stuck with underpowered tools like Excel when it came to data preparation. But all tools have their limits.A new wave of analytic value can come from uniting dozens or even hundreds of enterprise data sets. However, the magnitude of these challenges is beyond the scope of self-service data preparation tools. And the cost and complexity of traditional ETL approaches to many large scale data unification challenges renders them infeasible. Otherwise they would have done the job years ago.Toph Whitmore, Principal Analyst at Blue Hill Research recently published a report titled Connected Data Delivery: Combining Data Unification and Data Preparation. In it, he distinguishes these two related concepts and shows how they are complementary components of a big data value chain. He illustrates this model with real-world case studies where Tamr customers are using our platform for a new class of large scale data unification projects, and then handing off clean, mastered data sets to business users for ‘last mile’ data prep and analytics. Check out his report here.