Data Warehouse

Four common characteristics of big data 4V's

Variety Veracity Volume Velocity

Ineffective Direct Data Access

most data stored in operational databases did not allow users direct access, users had to wait to have their queries or questions answered by MIS professionals who code SQL

poor data quality

the data, if available, were often incorrect or incomplete. so users could not rely on the data to make decisions

Data-mining tools

use a variety of techniques to find patterns and relationships in large volumes of information

inadequate data usefulness

users could not get the data they needed, what was collected was not always useful for intended purposes

Big Data

A collection of large, complex data sets, including structured and unstructured data, which cannot be analyzed using traditional database methods and tools and includes the following four common characteristics Variety Veracity Volume Velocity

Extraction, transformation, and loading (ETL)

A process that extracts information from internal and external databases, transforms the information using a common set of enterprise definitions, and loads the information into a data warehouse

Data warehouse

A logical collection of information - gathered from many different operational databases - that supports business analysis activities and decision-making tasks

data bases are 2D - rows (entities) and columns (attributes) data warehouse is multidimensional, layers of rows & columns Dimension

A particular attribute of information

Data Mining Techniques CEAC

Classification Estimation Affinity grouping Clustering

Cube

Common term for the representation of multidimensional information

Structured Data

Contains a defined length, type, and format and includes numbers, dates, or strings machine-generated or human-generated

Data mart

Contains a subset of data warehouse information

Three organizational methods for analyzing big data

Data mining Big data analytics Data visualization

Data Visualization

Infographics Analysis paralysis Data visualization Data visualization tools Business intelligence dashboards Data artist

Unstructured data

Not defined, does not follow a specified format, and is typically freeform text such as emails, Twitter tweets, text messages

Data mining analysis methods POFR

Prediction Optimization Forecasting Regression

Data mining

The process of analyzing data to extract information not offered by the raw data alone

primary purpose of a data warehouse

aggregate information throughout an organization into a single repository for decision-making purposes

inconsistent data definitions

every department had its own method for recording data, so when trying to share info, data did not match and users did not get the data they really needed

Data Warehousing fixes the following problems

inconsistent data definitions lack of data standards poor data quality inadequate data usefulness ineffective direct data access

lack of data standards

managers need to perform cross-functional analysis using data from all departments, which differed in granularities, formats and levels