Humans are generating and collecting close to 3.5 quintillion bytes of data every day! This has given rise to data products–from BI dashboards to derived datasets, ML models, and more- bringing data closer to business users. Our Co-founder COO shares his thoughts around data products, and how each data product adds intelligence and efficiency to advanced analytics problems, speeding up analytical throughput by 10x.

1. 5 Things You Should Know
About Data Products
Q&A with Indrayudh Ghoshal,
COO of Scribble Data

2. What is a Data Product?

3. A data product is a self-contained, near full-stack
solution to an analytical problem. It takes disparate
raw data, enriches and scores it, and surfaces it to the
user.
It comes with guarantees around data correctness
and availability, and is customizable to the context
(business, user experience).

4. Who is Responsible for Data Products?

5. Technology teams may be involved, but data products should
be driven by the business in pursuit of a tangible outcome.
A data product is designed, owned and maintained by
business teams.

6. How Can You Build
Data Products at Scale?

7. You want to avoid inventing the wheel each time an advanced
analytics problem presents itself.
The problem is no longer with the scale of data, but the
number of use cases, and the application of relevant data to
each use case.
Build assets that can be combined into one or more solutions
to your data use cases. This not only speeds up analytical
throughput, but also helps maintain consistency and trust in
the process.

8. How Does Assetization of
Data Products Work?

9. The Assetization of data products is achieved at
three layers:
The composable interfaces through which the users
access the data product
The algorithms that model or score this data
The layer of features, or the attributes layer

10. What does this change?

11. ML-driven solutions to data use cases will be like water,
available at the turn of a tap.
This future will be built using data products that impact
business outcomes, and increase the analytical throughput of
teams manifold.
…more on this over at Scribble Data’s blog

12. Scribble Data's customers use Enrich to rapidly build data
products that address advanced analytics use cases. In the
near term, they’ve seen productivity of analytics teams
increase by upto 10x.
10x Faster

13. To learn more about how you can
get the most out of Data Products
powered by Scribble Data’s Enrich Platform,
write to us at hello@scribbledata.io
www.scribbledata.io
New York Toronto Bangalore