4 Data Security in Data Warehouses

ensures data in the data warehouse is correct, complete and consistent (if not, reports are unreliable)

ideal for real-time data access(users to query and analyze data on demand)

innovative, knowledge-sharing

2 Examples of Data Propagation

loading data into target system before transforming it

batch processing

relies on metadata and data virtualization techniques

traditional and widely-used data integration approach

central repository where businesses store and manage vast amounts of data from various sources for the purpose of analysis and reporting

transferring data from a central repository to different data marts

st9re the results of frequently executed queries to avoid redundant calculations

provides a clear understanding on how tasks are performed within an organization

within the organization and typically represent operational data

4 Examples of Middleware Integration

tackles the challenge of managing data scattered across various systems, formats and locations

Primary Purpose:support BI(business intelligence) activitiea

creates unified data layer that presents a single view of data from multiple sources

improve process efficiency, reduce human error and allows employees to focus on more strategic activities

encompasses the values, norms and practices that define the company's identity and guide it's bahavior

combining data from multiple sources to as single unified view

leverages the processing power of the target system(large datasets)

regular audits and reviews of organizational processes

users can access and manipulate data as if it were stored in a single location(simplify DI and reduce redundancy)

outside the organization and offer valuable insights into market trends, etc.

bridge between operational systems and the data warehouse

fundamental process in data warehousing

for big data scenarios

collaborative, family-like

help ensure that the company meets legal and regulatory standards

establishing these encourages employees to voice concerns about unethical practices with fear of retaliation

method used to visualize and map out the steps involved in business processes

rethinking the entire process from the ground up

provides valuable information for analysis and decision-making

allows users to query and analyze data from multiple sources as if in a single database

serves as a foundation for identifying inefficiencies and potential improvements in business process

competitive, result-driven

allows businesses to gain valuable insights into their operations, customer behavior and market trends

data consolidation historical analysis and BI applications

6 Techniques of Data Integration

consists of several key layers

these sources can be broadly categorized as internal and external sources

use execution plans to identify slow running queries and analyze their performance

acts as a single source of truth

shared values, beliefs, norms and practices that define an organization's identity and shape it's behavior

useful for large volumes of data or when real-time access to data is required

use of technology to automate repetitive, manual tasks within a business process

defines how data flows from various sources

subset of organizational culture focusing on the cultural aspects specific to for-profit businesses

robust code of conduct, paired with mandatory training on ethical behavior and decision making

innovative, dynamic

bureaucratic, structured

2 Techniques Used To Maintain High Data Quality

redesigning business processes to achieve dramatic improvements in performance

provides employees with clear guidelines on how to handle complex situations

cache frequently accessed tables/data sets in memory to speed up access times

blueprint that outlines the structure and components of a data warehouse system

bridge between different systems facilitating seamless data exchange and communication