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Data Analytics & Business IntelligencePresented by: Chris Ortega, MBA

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Born & raised in Indianapolis, INGraduate of IU – Kelley School of Business with Honor’sMBA from University of Indianapolis in Corporate Finance Manager, FP&A @ Weblink International8+ years experience in FP&A and Accounting/Finance Utilizing passions, skills, and talents to help others realize and achieve greatness!

About Me……….

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Presentation Agenda1. What is Data Analytics & Business Intelligence

(BI)2. Why is Data Analytics & Business Intelligence

(BI) Important? • Business Intelligence Spectrum

3. What is the decision cycle?4. Limitations of Data Analytics and BI 5. People Aspects of Data Analytics & BI 6. Process/Methods of Data Analytics & BI7. Technology/Systems of Data Analytics & BI8. Presentation Recap

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Data Analytics• “There were 5 Exabyte of

information created between the dawn of civilization through 2003, but that much information is now created every 2 days.” – Eric Schmidt, Google

Business Intelligence• “BI is about providing the

right data at the right time to the right people so they can take the right decisions.” - Nic Smith, Microsoft

What is Data Analytics & Business Intelligence (BI)?

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Why is Data Analytics Important?

Key Company Advantages for Data Analytics:• Faster, smarter, and better decision making• Foundation for scaled processes, insights, and analysis• Establishing a “Learning” Company Culture• Exploring new opportunities & mitigating threats/risks

Key techniques/methods for Data Analytics:• Data Management• Data Mining• Predictive Analytics• Data Cleaning & Storage• Multiple data source aggregation & integration

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Why is Business Intelligence Important?

Key Company Advantages for Business Intelligence:• Gain insights into customer behavior• Improve visibility and transparency into KPI’s• Turn data analytics into actionable information • Improve operational execution and efficiency

Key techniques/methods for Business Intelligence:• Business Planning & Direction• Data Storage and Information Processing• Technology focused • Customer segmentation/Forecasting/Budgeting• Accelerate the “Decision Cycle”

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Business Intelligence Spectrum

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Decision Cycle

The implementation of the decision cycle helps provide financial and non-financial insights (i.e. customer profitability, retention, addressable markets, etc.) The decision cycle allows organizations to use data to drive business decisions. BI tools such as Microsoft Power BI, Tableau, Qlik, and other tools help automate parts of the decision cycle.

Processes Data Inform

ationKnowle

dgeDecisio

n

Foundation ExecutionData Mining Data Analysis Learning

Data Analytics Business Intelligence

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Limitations of Data AnalyticsMost companies source data requires manually extracting the data then gathering that data into a spreadsheet.

Most excel spreadsheets are manual, meaning there is constant extracting and updating for new data.• Hourly, Daily, and Weekly data analysis and reporting requires a

lot of time to update• During the updating process, spreadsheets are prone to human

error.• Formula errors and troubleshooting is time consuming as you

have to identify the broken cell or formula to correct.

Employees have their own analysis and data sources so consolidation is difficult. Ad hoc analysis tasks to see the entire picture is difficult to perform.

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Lack to combine multiple data sets such as :• Access Databases• SQL Servers• Excel Documents• Teradata• Oracle• Salesforce• And other sources

Limitation of Formal BI Systems

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People Aspects of Data Analytics & BI“The evolution of finance is here to stay, and those professionals/companies adapting to the new finance frontier will be the ones who shape companies and industries for years to come.” – Young Salsa

People Challenges• Recruiting • Retaining• Developing• Talent Deficit• Change• Business Partnership • Finance Evolution

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Characteristics of Value Integrators: • Ability to adapt to

changing business landscape and strategy

• Utilizes technology along with high business acumen to lead strategy and operational execution

• Armed with Data Analysis skills (Excel, SQL, Data Mining, and Scaling Analysis)

People Aspects of Data Analytics & BI contd.

Source: IBM CFO-CIO Leadership Exchange Survey, May 2013

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Processes are the foundation for data driven decision making. Goal: to automate process to information to utilize high value FP&A activities.

Process/Methods of Data Analytics & BI

Technology becomes scalability avenue to share knowledge and learn.Goal: to produce framework for others to leverage in data decision making.

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2016 Business Intelligence & Analysis Magic Quadrant Detailed information around BI & Data Analytics solutions evaluated on:• Infrastructure• Data Management• Analysis & Content

Creation

Technology/Systems of Data Analytics & BI

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Trend of BI & Data Analysis Leaders

Highlights:• Oracle has moved completely outside of the Leaders

quadrant. • Microsoft continues to execute on completeness of vision

with other enhancements (Power Pivot, Power View).• Qlik decreases ability to execute and implement over the

years.

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Presentation Recap

The high value activities in the decisions cycle are accelerating the process to information phase, and spending more time and resources in turning that information into knowledge. This knowledge can then be used to make high value data drive business decisions.

Leveraging technology in conjunction with sound processes and data analytics allows companies to have access to data quickly and accelerate the decision cycle.

Understanding the role people, process, and technology plays into data analytics and business intelligence is important for all FP&A professionals.

Lastly, accept and embrace that data analytics & business intelligence is your friend and not your enemy.

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