Originally Published on Dec 15, 2014 The demand for new apps never stops … with frustratingly short deadlines. Developers are forced to make do without proper tools to help speed development while also addressing data issues as part of the development process. There is a better way!

1. Why Do
App Developers
Need a Data
Refinery?

2. The demand for new apps never stops
Requests pour in from IT to support
different business teams … with
frustratingly short deadlines
- Can you quickly get access to the data
you need?
- Can you leverage pre-built tools or
services to jump-start your process?
- Can your apps easily address privacy,
security, quality & governance needs?
. . . Would it help if you could do these things?

3. So application developers
- who wish they could quickly build cloud
applications
- and would like improve the quality and
functionality of their apps
- but lack access to data & services to
jump-start projects and address integration
and governance needs …
need a data refinery

4. A data refinery is . . .
a facility for transforming raw data
into information that is
clean,
timely,
relevant,
useful

5. A data refinery makes data access
as easy as . . .
getting fresh water from a tap
. . . for those who have the right permission

6. A data refinery makes its home . . .
on the cloud
. . . to be close to cloud-based applications
that consume data
. . . to provide low cost and flexibility

7. Some refinement approaches exist
Business-oriented
tools:
IT integration and
governance tools:
Hadoop-based and
integration-based
tools:
Easy to use by business
people …
Enterprise class …
Adequate for their own
special purposes …

8. But they leave big gaps & don’t work
for developers
Not useful for
developers
Too heavyweight and
infrastructure oriented
Too heavyweight; not fit
for app development
Business-oriented
tools:
IT integration and
governance tools:
Hadoop-based tools:

9. It’s time for data refinement
services
… light-weight, cloud-based, developer-ready services,
with exposed REST APIs
… that support activities such as:
loading data, provisioning masked data, profiling &
classifying data, performing secure on-premises load
to cloud targets, addresses cleansing, performing
probabilistic matching, etc.
… and that provide enterprise-level performance and
scalability, to ensure your apps run efficiently

10. What capabilities are delivered by
IBM’s data refinery, IBM DataWorks?
Capability
General
Availability Date Description
Load data December 12 Use an API to easily move data between cloud data
stores, such as SQL Database, Object Storage, and
IBM Analytics for Hadoop.
Provision masked data December 12 Use the data load API to mask sensitive data at the
source while it is moved.
Perform secure on-
premises load to cloud
December 12 Configure secure end points to access on-prem data
and use the data load API to move data between on-
prem and cloud data sources.
Access on-premise data using a secure gateway, and
use the data load API to quickly and easily access on-
premise data sources from the cloud.
Profile and classify data December 12 Gather information about data, such as column value
distributions or data types, and identify higher value
data attributes (i.e. e-mail addresses, National IDs,
etc.) so the app may take action – such as performing
masking. Also, classify each field in a domain.
Cleanse addresses December 12 Validate and improve the accuracy of location data by
standardizing US addresses. Enrich partial addresses
(such as incomplete ZIP code data).
Probabilistic match 1H15 Match customer information within and across sources.
Patented probabilistic fuzzy match algorithms return
accurate search results and relevancy scores to
confidently de-duplicate customer records.

11. It’s time for self-service
data refinement services to make
data work for you.
It’s time for IBM DataWorks™.
IBM
ibm.com/makedatawork
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