Why Do

App Developers

Need a Data Refinery?

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?

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

A data refinery is . . .

a facility for transforming raw data

into information that is

clean,

timely,

relevant,

useful

A data refinery makes data access

as easy as . . .

getting fresh water from a tap

. . . for those who have the right permission

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

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 …

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:

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

What capabilities are delivered by

IBM’s data refinery, IBM DataWorks?

CapabilityGeneral

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.

It’s time for self-service

data refinement services to make

data work for you.

It’s time for IBM DataWorks™.

IBMibm.com/makedatawork

#makedatawork