Introduction

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# BUS 320 Business Data Analysis and Interpretation

# Introduction

## Elizabeth Stanny

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<div class="my-footer"><span>http://bus320.estanny.com</span></div>

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# What is business analytics?

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>is the iterative process of learning from data, transforming data into insights for making better decisions

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.footnote[Source:  Introduction to the analytics mindset (slide 25), SCORE No. 01875-161US, www.ey.com/us/arc.]
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# Business analytics includes

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- Audit Analytics
  - [Delivering value with audit data analytics](https://www.journalofaccountancy.com/news/2020/jan/cpa-firm-value-audit-data-analytics-22751.html)

- Financial Analytics
  - [Three-minute guide](https://www2.deloitte.com/content/dam/Deloitte/global/Documents/Deloitte-Analytics/dttl-analytics-us-da-3minFinanceAnalytics.pdf)
- Human Resource Analytics
  * [How Analytics is Reinventing Human Resources](https://towardsdatascience.com/heres-how-analytics-is-reinventing-human-resources-1ad283fe7014)

- Marketing Analytics
    * [A Day in the Life of a Marketing Analytics Professional](https://towardsdatascience.com/a-day-in-the-life-of-a-marketing-analytics-professional-83dd45f2e702)

* Health Care Analytics
  * [Healthcare Big Data and the Promise of Value-Based Care](https://catalyst.nejm.org/doi/full/10.1056/CAT.18.0290)

]

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- Supply Chain Analytics
    - [How does supply chain analytics work?](https://www.ibm.com/supply-chain/supply-chain-analytics)

- Analytics for Government and Nonprofits
    * [Data-Smart City Solutions](https://datasmart.ash.harvard.edu/public-safety)

- Sport Analytics
    + [FiveThirtyEight](https://fivethirtyeight.com/tag/sports-analytics/)

- Tax Analytics
    + [Discover the value in your tax data](https://home.kpmg/au/en/home/insights/2017/05/discover-value-in-your-tax-data.html)

- Web Analytics
    + [Part of Internet marketing](https://en.wikipedia.org/wiki/Web_analytics)

]

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# What is analytics?

* extracting value from data

* limited in the past by software (e.g., `Excel`) and hardware

* today can use powerful tools (e.g. `R`) to more efficiently and effectively analyze a broader range of data and types of data than with (`Excel`)

* allow for enhanced insights from data to address business issues and transform the way decisions are made

.footnote[.font80[Adapted from: Introduction to the analytics mindset (slide 11), SCORE No. 01875-161US, www.ey.com/us/arc]]

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# The human element

Despite the increased sophistication of the data and the analytics, the most important aspect continues to be the **human element**, which includes:

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.center[.font200[critical thinking

and

judgment!]]

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.footnote[.font80[Adapted from: Introduction to the analytics mindset (slide 12), SCORE No. 01875-161US, www.ey.com/us/arc. Photo by Bacila Vlad on Unsplash]]

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# Learning objectives

1. Determine question want to answer with data analysis

2. Extract, transform and load relevant data (ETL process)

3. Apply appropriate data analytic methods

4. Interpret and present the results

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# 1. Determine question want to answer with data

*  Who are the relevant stakeholders?

* What are their objectives?

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# 2. ETL process (data wrangling)

* Extract (determine data will answer questions)

*  Load (import/read)

*  Transform (tidy)

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# 3. Apply appropriate analytic method

<table>
<caption>Question determines method</caption>
 <thead>
  <tr>
   <th style="text-align:left;"> Question </th>
   <th style="text-align:left;"> Type </th>
   <th style="text-align:left;"> Example </th>
  </tr>
 </thead>
<tbody>
  <tr>
   <td style="text-align:left;"> What are summarized characteristics of a data set without interpretation? </td>
   <td style="text-align:left;"> Descriptive </td>
   <td style="text-align:left;"> Have monthly profit margins changed in the last 2 years? </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Are there patterns, trends, or relationships within a single data set? </td>
   <td style="text-align:left;"> Exploratory </td>
   <td style="text-align:left;"> Are monthly profit margins related to underlying economic factors? </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Are there patterns, trends, or relationships in one data set that could apply to wider population? </td>
   <td style="text-align:left;"> Inferential </td>
   <td style="text-align:left;"> Are monthly profit margins for all companies related to economic factors? </td>
  </tr>
  <tr>
   <td style="text-align:left;"> Can measurements (features) predict for individuals (people or things) predict outcomes? </td>
   <td style="text-align:left;"> Predictive </td>
   <td style="text-align:left;"> Can economic factors predict a company's future profit margins? </td>
  </tr>
</tbody>
</table>

.footnote[.font80[Adapted from: https://ubc-dsci.github.io/introduction-to-datascience/index.html]]

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# 4. Interpret and present results

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### Interpret

- What do you see?

- Do you see what you expected to see?

- Do your results make sense to you?

- Is any further analysis required to meet your objective?

.footnote[.font80[Adapted from: Introduction to the analytics mindset (slide 41), SCORE No. 01875-161US, www.ey.com/us/arc]]

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### Present results

- How will your audience best receive the information?

- How much time you will have to present?

- Whether the presentation will be in person or virtual?

- What the best format of the presentation will be?

- Whether you have any additional recommendations for further analysis?

]

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# Use of storytelling to present results and persuade

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# Learning objectives for this class (once more)

- Determine question want to answer with data

- Extract, transform and load relevant data (ETL process)

- Apply appropriate data analytic techniques

- Interpret and share the results

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# R will be our main tool

#### Used in business

>As a CPA with Big 4 public company accounting and auditing experience, I think there is a HUGE opportunity for R to transform accounting/bookkeeping. ...What's more, you have companies like Deloitte, PwC, KPMG and EY exploring how blockchain and programming languages like R and python can revolutionize the audit cycle.

.font70[Source: David Sullivan.  Full post here https://community.rstudio.com/t/r-studio-for-accounting/4694/7?u=eliza]

#### Packages provide easy access to data

>R has been rising in popularity among researchers, economists, journalists and data scientists for the past several years, and data360r would allow the growing R community to easily access and analyze trade and competitiveness open data*

.font70[Source:World bank R package Data360R —data to the power of R https://blogs.worldbank.org/opendata/introducing-data360r-data-power-r]

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# R will be our main tool

#### Create reproducible results

>Data analysts who don’t organize their transformation pipelines often end up not being able to repeat their analyses, so the advice I would give to myself is the same advice often given to traditional scientists: **make your experiments repeatable!**

.font70[Source: Mike Driscoll, Founder & CEO at Metamarkets https://www.kdnuggets.com/2017/05/42-essential-quotes-data-science-thought-leaders.html/2]

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## Examples of R - telling stories with data

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### Washington Post

The Opiod Files

* [Stories based on data](https://www.washingtonpost.com/graphics/2019/investigations/dea-pain-pill-database/)

* [R package with code and data](https://wpinvestigative.github.io/arcos/)
]

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### Propublica

* [Where in The U.S. Are You Most Likely to Be Audited by the IRS?](https://projects.propublica.org/graphics/eitc-audit)

* [R code](https://github.com/propublica/auditData)
]

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.left-column[ ## R on Twitter
*  [#rstats](https://twitter.com/search?q=%23rstats)

* [#TidyTuesday](https://twitter.com/search?q=%23tidytuesday)

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<blockquote class="twitter-tweet"><p lang="en" dir="ltr">Why teach people in your company <a href="https://twitter.com/hashtag/rstats?src=hash&amp;ref_src=twsrc%5Etfw">#rstats</a>? So many reasons! R is:<br>- Free<br>- Reproducible<br>- Data manipulation is easier thanks to tidyverse<br>- Lots of online resources<br>+ more<br>- <a href="https://twitter.com/astroeringrand?ref_src=twsrc%5Etfw">@astroeringrand</a> <a href="https://t.co/CLbqGLCkLD">pic.twitter.com/CLbqGLCkLD</a></p>&mdash; Emily Robinson (@robinson_es) <a href="https://twitter.com/robinson_es/status/1275931344799858689?ref_src=twsrc%5Etfw">June 24, 2020</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script> 
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<blockquote class="twitter-tweet"><p lang="en" dir="ltr"><a href="https://twitter.com/hashtag/tidytuesday?src=hash&amp;ref_src=twsrc%5Etfw">#tidytuesday</a><br><br>Animal Tracking<br><br>Tracking the movement of Caribou in British Columbia, Canada.<br><br>Code:<a href="https://t.co/oGs9Nch9DT">https://t.co/oGs9Nch9DT</a> <a href="https://t.co/1BlO3wYbD3">pic.twitter.com/1BlO3wYbD3</a></p>&mdash; Adyatama (@Argaadya1) <a href="https://twitter.com/Argaadya1/status/1276054950003437571?ref_src=twsrc%5Etfw">June 25, 2020</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script> 
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<blockquote class="twitter-tweet"><p lang="en" dir="ltr">My first contribution to <a href="https://twitter.com/hashtag/TidyTuesday?src=hash&amp;ref_src=twsrc%5Etfw">#TidyTuesday</a> <a href="https://t.co/2fSPqxV2de">pic.twitter.com/2fSPqxV2de</a></p>&mdash; Wangui Ngina (@ngina_wangui) <a href="https://twitter.com/ngina_wangui/status/1274042941967929350?ref_src=twsrc%5Etfw">June 19, 2020</a></blockquote> <script async src="https://platform.twitter.com/widgets.js" charset="utf-8"></script> 
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### Big data V's according to IBM]

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<img src="images/5Vs.png" style="width: 50%" />

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