Data Management

Ppt, Textbook, Attendance Q's

4 Reasons Data Management Matters

1. AI Systems are only as good at the data they consume

2. The shift from ‘big data’ to ‘smart data’

3. Data readiness is the #1 barrier to scaling AI

4. Good data management is NOT OPTIONAL.

Internal v. External Memory

Internal memory is like the stuff in your brain, short-term.

External memory is like a calendar - essentially a unique way of storing data and suppporting it’s rapid retrieval.

Individual memory systems illustrate some features common to all data management systems. What are they?

• There is a storage medium. Data are stored electronically in each case.

• There is a structure for storing data. For instance, the address book has labeled spaces for entering pertinent data.

• The interface is organized for rapid data entry and retrieval. A calendar is stored in date and time sequence so that the data space for any appointment for a particular day can be found quickly.

• The selection of a data management system frequently requires a trade-off decision. In these examples, the trade-off is screen dimensions versus the amount of data that can be seen without scrolling. For example, you will notice the address book sample screen is truncated and will need to be scrolled to see full address details.

Internal memory is __

fast, small, and convenient

External memory is

slower to reference, and not always convenient

TPS

Transaction Processing System - Collect and store data from routine transactions

MIS

Management Information System - Convert data from a TPS into information for planning, controlling and managing an organization

DSS

Decision Support System - Support Managerial decision making by providing models for processing and analyzing data

BI

Business Intelligence- Gather, store, and analyze data to improve decision making

OLAP

Online Analytical Processing - Provide a multidimensional view of data

DM

Data Mining - Use of statistical analysis and artificial intelligence techniques to identify hidden relationships in data

ML

Machine Learning - Using software to make decisions or recommendations traditionally made by humans.

Desirable Attributes of Data

Transportable

Secure

Accurate

Timely

Relevant

Problems with Data Management Systems

Redundancy

Lack of Data Control

Poor Interface

Delays

Lack of Reality

Lack of Data Integration

The Data Deluge

Overwhelming flow of data and information. The volume, velocity, and variety of data make manual curation impossible.

AI tools amplify the good and bad data

External memory extends

Internal memory

The Information Cycle

The diagram shows a continuous cycle of how organizations use information systems:

1. Transactions → Handling the present (TPS)
   Systems capture day-to-day business activity.

2. Data → Preparing for the future
   Collected data is analyzed using tools like BI, data mining, DSS, EIS, MIS, OLAP to support decisions.

3. Remembering the past
   Results are stored in databases and data warehouses for long-term use.

4. New business systems
   Insights lead to improved or new systems, which generate more transactions.

Components of Organizational Memory

• People / Conversations

• Tables / Documents

• Video / Images / Graphics / Multimedia

• Models

• Knowledge / Decisions

• Specialized memories

Managerial work is

• Fragmented

• Brief

• Frequently Disturbed

• High Velocity

• Action oriented rather than comtemplative

Two characteristics of Information

Hardness

Richness

Informatino Hardness

Just know this

What is the biggest barrier to scaling AI systems with organizations?

Data readiness