zaldy.adrianto@unpad.ac.id

Data Warehousing

Data Warehouse

Subject oriented, integrated, time variant, non-updatable collection of data used in support of management decision making processes

updatable collection of data used in support of management decision making

Subject oriented! !

Data warehouse is organized around the key subjects (or high level entities) of the enterprise. !

major subjects may include customers, patients, students, products and time

Integrated!

The data housed in the warehouse are defined using consistent naming conventions, formats, encoding structure, and related characteristics gathered from several internal systems of record.

Time Variant!

Data in the data warehouse contain a time dimension do that they may be used to study trends and changes

Non-updatable!

Data in the data warehouse are loaded and refreshed from operational system, but cannot be updated by end users.

Data Warehouse

Data warehouse is not just a consolidation of all operational database in an organizations

its focused on business intelligence, external data, and time-variant data.

data warehouse is a unique kind of database.

Data warehousing

Process whereby organization create and maintain data warehouse and extract meaning and inform decision making from their informational assets.

Key advances of data warehousing

Improvements in database technology

Advances in computer hardware

(affordable mass storage and parallel computing)

Emergence of end user computing

advances in Middleware Products

The Need for Datawarehousing

Business requires an integrated, companywide view of high quality information

The IS department must separate information from operational systems

Need for companywide view

Data in operational system are typically fragmented and inconsistent

Distributed on variety of incompatible hardware and software platform

Need to separate operational and informational System

Operational systems: A system that is used to run a business in real time, based on current data.

Informational Systems: Systems designed to support decision making based on historical point in time and prediction data.

Primary factors in separating operational and informational

systems

A Data warehouse centralizes data that are scattered!

A properly designed data warehouse adds value to data by improving their quality!

a separate data warehouse eliminates much resources when informational are confounded with operational processing

Big DataEvery day, we create 2.5 quintillion bytes of data so much that 90% of the data in the world today has been created in the last two years alone. This data comes from everywhere: sensors used to gather climate information, posts to social media sites, digital pictures and videos, purchase transaction records, and cell phone GPS signals to name a few. -IBM-

Big data and Business

Volume. as 2012, 2.5 exabytes data created each day, and doubling every 40 Months!

Wallmart create 2.5 Petabytes data every hour from its transaction

Big data and Business

Velocity. The speed of data creation is more important than the volume!

Macys used data from mobile phones in parking lot even before the sales occurred

Big data and Business

Variety. Big data takes the form of messages, updates, and images posted to social network, GPS signals, and many more.!

each of us is walking data generator, and the data often unstructured (not organized in database).

Benefits

Smarter decisions Leveraging new sources of data to improve the quality of decision-making.

Faster decisions Enabling more real-time data capture and analysis to support decision making at the point of impact, for example, when a customer is navigating your website or on the telephone with a customer service representative.

Decisions that make a difference Focusing big data efforts on areas that can provide true differentiation.

Jim Hare

Program Director, IBM Big Data Product Marketing

Challenge of Big Data

Leadership

Talent Management

Technology

Decision Making

Company Culture

Leadership

Big datas power still need for vision or human insight

business leader must spot a great opportunity, and understand the market.

Talent Management

Data analyst with ability to cleaning and organising large data set

Computer scientist with visualisation skills

Technology

Technology to handle large volume of data and the variety of big data have improved recently.

however this technology require a new skill.

Decision Making

Information that is created needs expertise to solve the problems

Company culture

Move away from acting solely and instinct

Need to change the habit to spiced up

report with data ?