Mid August 2015 - Data Analytics

1. Fundamentals of
Data Analytics
Class Outline
Prepared by Daniel Meyer
President & Founder of
DMAI – Decision Making, Analytics & Intelligence

2. About the Presenter
Dan Meyer, the CEO of DMAI has over 20
years of experience in the Higher Education,
Business Process Outsourcing and
And Financial Services.
● BPO Elite - Chief Executive Officer
● Wells Fargo Bank - Senior Analytics Consultant
~ Innovative and Enchanting Trainer
~ Top Analytics Expert in the Country ~ BPO Industry Leader
~ Marketing Strategy Wizard ~ Outsourcing Leader
~ Business Strategy Builder ~ Competitor Intelligence Chief
~ Business Intelligence Ninja ~ Process Improvement Guru
 Bachelor’s Degree in History with minor in International Studies
 Master’s Degree in Education

3. Agenda
Topics covered in the training include:
• What is Data Analytics?
• The current state of Data Analytics in the Philippines
• Self-Assessment of our own Data Analytics
• Finding the Right Data at the Right Time
• Big Data and Data Warehousing
• Descriptive, Predictive, and Prescriptive Analytics
• Business Intelligence and Data Visualization
• Using Data Analytics to Drive Decisions

4. What is Data Analytics?

5. The Concept of Analytics
Per Wikipedia, the definition of analytics is
simply the discovery and communication of
meaningful patterns in data.
Definition
While most people have an idea of what
Analytics is: data, analysis, metrics, and
business intelligence are just the start… it is an
abstract concept that is difficult to summarize
in a sentence or two.

6. The Concept of Analytics
When you look at any successful business, odds
are that they have solid data analytics in place.
As opposed to businesses that are run based on
intuition or gut feel, businesses that invest in
data analytics generally make better decisions.
I often see it quoted by analytics savvy
companies like IBM that, companies who use
analytics are 10x more efficient and 33% more
profitable then ones who don’t.

7. The Concept of Analytics
Data analytics is generally considered to be
the examining raw data with the purpose of
drawing conclusions about that information.
Data analytics is used in many industries to
allow companies and organization to make
better business decisions.
Let’s take a minute to discuss how we
each use data analytics?

8. The Concept of Analytics
Analysis of data is a process of inspecting,
cleaning, transforming, and modeling data with
the goal of discovering useful information,
suggesting conclusions, and supporting
decision-making.
Inspecting Data
Cleaning Data
Transforming Data
Modeling Data
Discovery of Patterns
Making Suggestions

9. The Concept of Analytics
Endless stream of
data with immense
volume, variety and
velocity coming form
global markets and
from multiple social
media platforms,
present
opportunities of
information and
analytics value.

10. The Concept of Analytics
Recent innovations have developed new tools
and techniques enabling business management
and public institutions to adopt business
analytics into their organizational processes and
information ecosystems.
In line with these innovation, we are offering
this course to give attendees a step up in the
various aspects of data analytics.

11. The Concept of Analytics
This training course, the Fundamentals of Data
Analytics, comes out of a need for more Filipino
companies to being a higher level of data
analytics into their business. Often data in not
being used in optimal ways.
Participants will leave with an overview of the
current trends in data analytics that drives
today’s businesses.

12. What is the current state
of business analytics in
the Philippines?

13.  There is a huge gap between
available analytics talent and the
needs of the market.
 There are over 2,000 analyst
positions posted everyday on
jobstreet.com.ph
How DMAI Uses Analytics

14. How DMAI Uses Analytics
“The world is currently witnessing a
fundamental reorganization in the
way services are delivered to
customers. This is what is behind the
movement to outsource. It’s a lot
more than just saving money by
shipping jobs overseas.” - Harvard
Professor Robert E. Kennedy

15. How DMAI Uses Analytics
The globalization of services, in which different tasks
are being carried out by different individuals in
different locations, is about gaining access to the best
combination of talent, resources and markets.
• Technological Innovations like easy access to the internet
and stored data.
• Emerging Market Growth in traditionally closed markets
• Global Macroeconomic Liberalization of government polices
toward trade
• The Corporate Imperative to both reduce costs and improve
quality
• The Convergence of a Global Business Culture based on the
English language and American business models.

16. The Concept of Analytics
An ANALYST is a person who analyzes and
skilled in analysis.
Four Character Traits that most analysts have:
• PASSION for helping people solve real
problems
• KNOWLEDGE of the business being analyzed
• EXPOSURE to thinking analytically and
problem solving tools
• EXPERIENCE using data to solve problems

17. The Concept of Analytics
Certain personality types most analysts have:
• reflective
• intuitive
• deep-thinkers
• and able to make quick judgments
The International Institute for Analytics and Vendor
Talent Analytics, Corp. surveyed 302 analytics
professionals last summer.
Curiosity came out as the top skill in a study of the
characteristics of analytics pros.

18. Data Scientists
Enough has been said about how and why Data
Scientist is the Sexiest Job of the 21st Century
and why we need them to extract insights from
data to have actionable analytics.
The unique blend of skills required for this role is
being debated and almost everyone around the
globe who is associated with Big Data, Analytics
and Visualization has opinion on this topic.

19. Data Scientists
DJ Patil, one of the world’s 7 most powerful Data Scientists according
to Forbes. According to him, “A data scientist is that unique blend of
skills that can both unlock the insights of data and tell a fantastic
story via the data.”

20. Self Assessment
of Your Own Analytics

21. The next step is to assess the analytics culture of your
organization. Which of the following best describes the way
analytics is utilized where you work.
• Level 1 – No analytics at all.
• Level 2 – Only a few people use analytics and most key
management decisions are not made based on data, but on
experience
• Level 3 – Some people use some analytics to make some
decisions, but its generally inconsistent across the organization.
• Level 4 – Most decision makers have access and generally use
analytics. Several key team members have strong analyst
backgrounds.
• Level 5 – Every team member from top down knows analytics,
has access to the data they need and are empowered to take
action on it.
Analytics Assessment

22. Finding Data…
Especially Unstructured
Data on the Internet is A
Super Hard to Find Skill

23. Finding Data
Most Data is Unstructured, meaning its not
easily accessible and stored in an internal
database.
In the book the Accidental Analyst, the authors list three steps
in collecting data:
1. Identify your data.
2. Inventory your data.
3. Integrate your data.

24. Finding Data
Analysis is truly something that means
something different to everyone. However we
can divide analysis into three phases.
Step #1 . Identify. Finding the Data or
Writing Requirements. - Raw numbers have to
be filtered for the most part the data. Take
numerous pieces of data and extract what you need.
Solid requirements help maximize the time to focus
on analysis.

25. Finding Data
Step #2 Inventory > Analyzing the Data or
Crunching the Numbers. You started with a
problem or a question, you compiled data, now you
need to find the answer and come up with potential
solutions.
There is not sure fire way to do this.
It’s a combination of training, knowing the data,
understanding the business and most importantly
knowing what your audience is looking for.

26. Finding Data
Step #3 Integrate > Adding Narrative and
Visuals or Telling the Story. This is where being
an analyst takes science and turns it into art.
Now that you have the data and your analysis is
complete and you have answered the original
question, you need to turn the data into something
that tells a story.
Leaders, Owners and Managers will make decisions
based on your data based on how you present it.

27. Big Data and Data
Warehousing

28. Big Data & Recruiting
Big Data is the buzzword of the year.
Every leader — whether they’re managing a
small team or are at the helm of a multinational
corporation with thousands of employees — is
wondering how they can use Big Data to better
get to know their people, to create a setting
that better suits their needs and, in turn, drive
recruitment and retention.
What do you know about Big Data and how its
being used in your business?

29. Every company has untapped analytical
resources. Every company has the
potential to be Decoded.
Data has become such a plentiful resource that
many companies are producing many streams
of data already without capturing any useful
insights. In that respect, identifying data
sources and analytical resources can provide
guidance in understanding your organization’s
needs and capability to adopt a talent-centric
data-driven approach.
Big Data & Recruiting

30. Knowing where to go to find the data you need is
one of the most important keys to being a successful
analyst.
There are three basic areas where you can go to find data:
1. Private Company Databases and sources
2. Public Databases and sources
3. The Internet
Knowing where to quickly find data, is a
key to an analyst’s success.
Internet Research

31. All the major companies have databases and data
warehouses where they store billions of points of data.
Each company treats its data a little different, but you can expect them
to fall into the following categories:
1. Proprietary Databases. All of the data used for analysis is kept in databases that
are built and maintained by an internal IT team. They may use heavily personalized
commercial software.
2. Off the Shelf Databases. Most data is housed in a commercial database solution
like Oracle, Teradata, MS Access, etc. where IT team often work in partnership with
the database manufacturer.
3. External Databases. The company does not have its own IT team and receives its
data from external resources. Usually analysis is conducted via a connection to the
data through the vendor.
Databases and Data Warehouses
Finding Data

32. Background
Per Wikipedia, Unstructured data (or
unstructured information) refers to information
that either does not have a pre-defined data
model or is not organized in a pre-defined
manner.
Unstructured information is typically text-heavy,
but may contain data such as dates, numbers,
and facts as well.

33. Challenges

34. Challenges
Recent discussions about Big Data are showing
that about 80-90% of data currently being
captured by businesses is unstructured.
Just two year ago it was 50% and five years ago
about 20%. The boom is unstructured data
storage is fundamentally changing business
analytics as we know it.

35. Discussion about
Descriptive Analytics,
Predictive Analytics, and
Prescriptive Analytics

36. The Three Types of Analytics
Descriptive Analytics looks at the past to
explain the present.
Predictive Analytics uses past data to model
potential futures.
Prescriptive Analytics use past data to direct
variable present and future options.

37. Descriptive Analytics
Definition: Answers the question what
happened the business.
Primary Use: Looks at current business
situation.
Software Applications: Business Intelligence
Tools
How do we see descriptive analytics
being used around us every day?

38. Predictive Analytics
Definition: It takes data and extrapolates
patterns to predict likely outcomes. Past,
Present, Past Present, Future
Primary Use: To predict outcomes to mitigate
risk
Software Applications: Modeling software that
allows complex hypothetical simulations.
How can predictive analytics be used to
improve things here in the Philippines?

39. Prescriptive Analytics
Definition: Finds the best course of action for
a given situation.
Primary Use: Narrows decision-making by
giving more educated choices.
Software Applications: Advanced modelling
applications that account for multiple
variables in analysis and forecasting.
What are some ways Prescriptive
Analytics could be used here in the
Philippines?

40. Business Intelligence
And
Data Visualization

41. Business Intelligence aims to support better
business decision-making. Decisions drive
organizations. Making good decisions at critical
moments is the key to efficient operations, profitable
products and satisfied customers.
If information, processes, and tools are lacking, more
than 35 percent of the top 5,000 global companies
will regularly fail to make insightful decisions about
significant changes in their businesses and markets.
Business Intelligence Tools allow analysts to take data
and turn it into actions.
Business Intelligence

42. Business Intelligence
Business intelligence (BI) refers to computer-
based techniques used in identifying, extracting,
and analyzing business data, such as sales
revenue, market opportunity or product
performance.
Some of the BI market
leaders include:
• IBM-Cognos
• Microsoft Objects
• Tableau
• Qlikview
• Yellowfin

43. Data Visualization
Data visualization is simply taking data and converting it
to visuals like pie charts, line graphs, sales charts, etc.
However in the hands of a good analysts you can build
systems and processes by turning raw data into a visual
tool. That makes the decision making quicker and with
less error.
Best analysts are the ones who can visualize data and
use tools to add a story telling component to their
analysis.
A picture is worth a 1000 words, just like a good pie
chart is worth 1000 rows of excel data.

44. Business Dashboards
Wikipedia definition of a business dashboard: "An easy to
read, often single page, real-time user interface, showing a
graphical presentation of the current status (snapshot) and
historical trends of an organization’s Key Performance Indicators
(KPIs) to enable instantaneous and informed decisions to be
made at a glance."
1. Easy to Read
2. Singe Page
3. Real Time
4. Graphical Presentation
5. Current Status
6. Historical Trends
7. KPIs
8. Make Decisions

45. Using Data Analytics to
Drive Decisions

46. Decisive
Keys to Decision Making
Most decision are made in an instant and are often just a choice
between two options.
In the book the Decisive, the authors list four tips:
1. Widen Your Options.
2. Reality-Test Your Assumptions.
3. Attain Distance Before Deciding.
4. Prepare to be wrong.

47. Enchantment – The Art of Changing
Hearts, Minds and Actions by
GUY KAWASAKI
~He was the chief evangelist at Apple and was behind
the success of the Macintosh line in the 1980’s
~He defines ENCHANTMENT as the “state of
transformation in ones perception of things”.
Enchantment is not about manipulating people,
but in altering the way they relate to you and
whatever it is you are selling.
• bring about a voluntary,enduring and delightfulchangein the people you
interactwith.
• need to do more thanjust relay facts and offer datapoints

48. There are three pillars of enchantment:
 Likability
 Trustworthiness
 Great cause.
• To achieve likability, you need to accept others and always
find something to like in them.
Example – Bill Clinton
• To achieve trustworthiness, you need to be knowledgeable,
competent, create win-win situations and do the right thing.
Example – Superman is a hero, Batman is an anti-hero
• To truly enchant someone, you need a great cause. You need
to communicate why it is great, in short, simple and swallow
able terms.
Example – Analytics using something like Tableau

49. 8/24/2015
CONNECT WITH US!
• www.facebook.com/dmaiph
• #bpoelite1
• http://ph.linkedin.com/pub/dan-
meyer/4/771/675
• www.dmaiph.wordpress.com

50. Now go out and analyze something!!!!!!!
Congratulations!
You have completed
Fundamentals of
Data Analytics.