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BUSINESS INTELLIGENCE/

ANALYTICS

Brenda Woods

John Williams

Daniel Bailey

Breia Stamper

Overview

Definition BI Overview Benefits BI Tools Examples Future

What is Business Intelligence?

Variety of software applications used to analyze an organizations row data

BI as a discipline is made up of several related activities: Data Mining Online analytical processing Querying Reporting

Data analysis process is aimed at boosting business performance

Helps users back up - with hard numbers- business decisions BI is now a requirement for businesses looking to stay

competitive

Short video of Norfolk Southern Railway and how they’ve used Oracle BI.

Benefits of Business Analytics

Eliminate guesstimating – By providing more accurate historical data, real-time updates, synthesis between departmental data stores, forecasting, trending, and predictive analysis

Get answers faster – BI users can quickly get answers to business questions rather than spending hours reading through printed reports

Additional Benefits

Get reports on the fly – Many of the business intelligence software vendors are able to access key business metrics, reports, and dashboards on mobile devices

Get insight into customer behavior – BI software allows companies to see what customers are buying, giving them the ability to turn knowledge into profit

Even More Benefits

Streamline operations – With detailed reports on business performance, organizations can easily see where they need to make changes

Improve efficiency – By not wasting significant time looking for data within various departmental sources

Business Intelligence Design

Finance Supply Chain

SharePoint Website

ETL Process

Data Warehouse

Data Mart Data Mart Data Mart Data Mart

Ad Hoc Reporting

OLAP Reporting Engine

Scorecards Dashboards Tabular Reports

Common Obstacles

Structured & Unstructured Internal & External Don’t have the data  Many Data Sources  Data overloading Data Access

BI Tools

How do we get to this data? How do we integrate it? How do we present it?

BI Tools

Three CategoriesData ManagementData DiscoveryReports

Data Management

○ Data Extraction/IntegrationRead and extract subsets of dataDifferent Data sourcesOrganize Data

○ Data Quality/TransformationCleansed Data – garbage in garbage outData Consistency – standardizedData Integrity -must match data source

Data Management

Data Discovery Applications Provides an avenue for the users to get to their

data Users are able to slice and dice the data,

identifying patterns that are unknown by traditional reports.

Structured to help users make sense of the data

Data Mining

Examination of large volumes of data and finding patterns and/or relationships that haven’t been discovered.

Help predict behaviors and future trends

Online Analytical Processing (OLAP) Organized hierarchically Uses multidimensional datasets Enables users to compare the data from

many different points of view Utilized by Managers and Power Users

Predictive Analytics

Uses historical data combined with transactional data to help identify risks and opportunities for the future.

Forecast of what Might happen in the future

Allows organizations to become proactive and forward looking.

Reporting Application

Visualization is a graphical representation of data and can help users understand the data in a more insightful way

Dashboards help managers focus on the metrics that are most important

Scorecards takes dashboards one step further by attaching a numerical weight to the performance and maps the progress toward goals

Visualization

Dashboards vs. Scorecards

BI Platform Capabilities

Business User Data Mash up and Modeling

Internal Platform Integration BI Platform Administration Metadata Management Cloud Deployment Development and Integration

BI Platform Capabilities Free-Form Interactive Exploration Analytic Dashboards and Content IT Developed Reporting and Dashboards Traditional Styles of Analysis Mobile Collaboration and Social Integration Embedded BI

Pull Rate for Order Pickers

9/1

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Average

Derrick, Ingram

Goal

Johnson, Anthony

Lauderdale, Robert

Lawrence, Boston

Lemons, Derrick

Owens, Roderick

Williams, Joseph

Business Analytics You have to understand

the history and current aspects of business analytics to understandthe future

These are some of thelarger companies that offer business analyticsoftware.

Popular Programming Languages Oracle is mostly C and C++ SAP is written in ABAP SAS is programmed in C While some statistical companies use

the programming language R, which is based off of C, C++ and Fortran

Future of Business Analytics

Cheaper data storage and processing methods increase use of BA

Helps us to develop more accurate goals for the present and the future

Validate or disprove hypothesis through the use of big data

Future of Business Analytics Collection of larger sets of data then

previously collected before. Transitioning from 32 to 64 bit software

and applications Running queries directly in mainframe

ram Able to use centralized data centers

remotely due to faster internet speeds

Going Mobile

Faster processors then before Faster connection speed More ram Higher resolution screen and cameras Social movement to be reachable

anywhere and any way

The simple picture text that we were so proud to be able to finally in recent years not to long ago has now moved on to live video chats.

Getting an email on the phone has gone to full blown meetings and presentations on the go

Data Collection

Instead of just collecting information on how well your employee has preformed in trying to get a good to the end user you find out how the end user uses the product, how they feel about it, any problems that they have with it, and how, where and why they use it.

Business Analytics Is needed to

understand thebigger picture while still notlosing focuson the everyday goals.

Questions

top related