April 28, 2015Virginia Tech

Data Analytics

“Analytics is the combustion engine of business, and it will be necessary for organizations that want to grow, innovate and optimize efficiency. Given its far-reaching impact, it’s one of the few software markets that thrive even in adversity”

Rita Sallam, BI Analyst, Gartner

What is Data Analytics? How would you define it

Data Analytics Maturity Model

Tools, Technology and Techniques

PwC

Draft

Visualization

Dashboarding

Trending & comparisons

Data

Financial, Operational Structured, Unstructured,

Internal, External

Analytics; discovery and communication of meaningful patterns in data

Big data; collection of large and complex data sets

Speed and portability; available anytime, anywhere

Characteristics of analytics today

PwC

Draft

Analytics

Data Management Monitoring

Visualization

Core Technological Components and Key Vendors

To have an effective analytics program for a complex organization, there is no “one size fits all” for technology. An analytics toolbox is necessary to bring the highest value

PwC

Spotfire Qlikview TableauLavastorm

What tools are being used?Major vendors within the analytics space

PwC

Comparison

Tools

Capacity

Ease of use

Availability

Analytic Capabilities

Documentation

Microsoft ExcelMicrosoft Access

ACL

• 65,536 rows by 256 columns (pre ’07 versions)• 255 chars per field

• 2 GB database• 255 fields (columns)

•Unlimited

• Standard, easy to use office application

• Training is required

• Requires basic training• Menu based

• Standard installation on PwC laptop

• Standard installation on PwC laptop

• Standard installation on PwC laptop license

• Data analysis toolkit• Built-in functions

• Built in functions• Great for joining tables

• Complete set of preprogrammed analysis

• To be done manually by user

• To be done manually by user

•Log file is documents every

step continuously

Excellent Satisfactory Poor Very Poor Good

Tool choice should

depend on user

expertise, data to

analyze and analysis to

be performed

PwC

ACLACL

Audit Command Language

Point-and-click based software with ability to create executable scripts

Commonly used for data analysis related to fraud detection among Big Four firms

ACL can be applied to assist with:

Journal Entry Testing

Internal Audit Testing

Record Sampling

PwC

Industry Focus

• Media

• Entertainment

• Retail

• Financial Services

• Insurance

• Pharmaceutical

• Healthcare

• Technology

• Industrials

• Consumer Products

Data Auditing is“Industry Agnostic”

PwC

Business AnalysisAudit Support

• SAS99 Journal Entry Testing• Testing of Unrecorded Liabilities• AR Liquidation analysis• Revenue Recognition Re-performance• Vendor and Accounts Payable Analysis• Fixed Asset Analysis• Inventory Testing Analysis

Non-Audit Support

• Travel and Expense Investigation• Vendor Master Data Analysis• Inventory Analysis• Database Development• Process Automation• Data Migration Validations

PwC

DraftAnalytics Methodology - AVAD

Acquisition

Acquisition: Gather data from client systems; collect system business rules through interviews and available documentation

DeliveryDelivery and Documentation: Reports, transformed data for target systems, graphic representation, models, etc.

ValidationValidation: Assess data; ensure data adheres to business rules; reconcile

Analysis: Analyze data to address business issues (fraud, errors, buying patterns,target model support, etc.)

Analysis

AcquisitionValidation

Delivery

Analysis

PwC

Draft

IA / BasePaksTechnology

12

Client Data

Raw Data

Base

Pak

Simplified Data Model

Sta

nd

ard

ized

Test

s, A

naly

tics

Standardized Results

StandardizedAnalysis

Standardized

Reporting

Standardized Dashboards

Why IA / BasePaks

Repeatability, Sustainability

Efficiency

Reliability

Foundational Data Analytics (Demo)

“The transformational change occurring in organizations today is dependent upon adopting insight from data ... Everyone is now an analyst. ”Data Science Central

“The transformational change occurring in organizations today is dependent upon adopting insight from data ... Everyone is now an

analyst. ”Data Science Central

“Last year people stored enough data to fill 60,000 Libraries of Congress...”

The Economist

“90% of the world’s data was created in the past two years ” IBM

“…Data volume will double over the next two years” Gartner

Drivers of Data

Auditing

Common Data

Challenges

Types of Data

Embedding Analytics throughout the Lifecycle

Data Analytic Tools and Visualization

Benefits of Data Auditing

AICPA’s Audit Data Standards

How Can Analytics Help?