1. Business Intelligence in the age of analytics
Printed on 1/27/2018
Business Intelligence in the age of analytics
10/14/2016
Deliver Solutions, Deliver Careers, Deliver Results
© 2013 Computer Technology Solutions, Inc.

2. Agenda Business Intelligence Big Data Modern BI and Analytics
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Agenda
Business Intelligence
Big Data
Modern BI and Analytics
Takeaways
© 2013 Computer Technology Solutions, Inc.

3. Today’s Speaker Yissel Espinosa Cervantes Consultant CTS
Printed on 1/27/2018
Today’s Speaker
Yissel Espinosa Cervantes
Consultant
CTS
@YisselEspinosa
© 2013 Computer Technology Solutions, Inc.

4. Business Intelligence
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Business Intelligence
Business Intelligence
© 2013 Computer Technology Solutions, Inc.

5. Business Intelligence
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Business Intelligence
Business Intelligence (BI) refers to technologies, applications and practices for the collection, integration, analysis, and presentation of business information. 
BI solution supports decision making, transforming data into usable and actionable business information.
© 2013 Computer Technology Solutions, Inc.

6. BI Solution Architecture
Printed on 1/27/2018
BI Solution Architecture
Explain a BI Solution Architecture. This is a traditional (classic) example, but it is different in every organization.
Explain: -ETL
-DW
-dimensional models / cubes
-OLAP / analytical techniques  mainly data mining
-reporting, heavily spreadsheets for most of the organizations, then transitioning to Reports, and Dashboards.
STORY! Provide example of my first internship, and how the users were not ready for a DW yet. You always need to SERVE the business.
--- Other meanings:
LOB Line of Business
OData (Open Data Protocol) is a standard for building and cosuming RESTful APIs
© 2013 Computer Technology Solutions, Inc.

7. BI terminology DW Analytics BI BI & Analytics ETL Reporting
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BI terminology DW
Analytics BI
BI & Analytics
ETL
Reporting
Most of the recent research and articles stay away from Data Warehouse or BI alone since they tend to refer to the traditional (“old”) analytical approaches. The term widely spread recently is ANALYTICS, which was introduced in the late 2000’s to refer to the key analytical component of BI.
Therefore, everyone is using it in one way or the other, with terms like Business Analytics, BI & Analytics, Advanced Analytics, etc..
The terms BI, DW, Analytics, Business Insights, BI & Analytics, are used in different scenarios, depending of the components of a particular solution. Frequently, some of the terms are used interchangeably, adding more to the confusion.
“I DO like to use Business Intelligence, or just BI, although I may use BI and Analytics to refer to the modern approaches in contrast to the traditional”
© 2013 Computer Technology Solutions, Inc.

8. Big Data Big Data © 2013 Computer Technology Solutions, Inc.
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Big Data
Big Data
Big data has become a very hot topic, skill, and buzz word in technology. Many companies are claiming themselves as leaders in big data, and there is no better time to create a career around data and this new technologies.
What is big data?
“Is there anyone that would like to give us an idea of what they understand by “Big Data”?”
The truth is: there are as many definitions as you can find. There is an article on Opentracker.net that summarizes over 30 distinct definitions. Here you have some of them:
© 2013 Computer Technology Solutions, Inc.

9. Printed on 1/27/2018
Big Data
“Big data is when the size of the data becomes part of the problem”
"Big data is data that exceeds the processing capacity of conventional database systems. The data is too BIG, moves too FAST, or doesn’t fit the structures of your database architectures”.
definitions from Opentracker.net
“I like this simple definition: “Big data is when the size of the data becomes part of the problem””
Big data is data that exceeds the capacity of conventional systems. The data is too BIG, moves too FAST, or doesn’t fit the structures of your database architectures
© 2013 Computer Technology Solutions, Inc.

10. Big Data Volume Variety Velocity
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Big Data
Volume
Variety
Velocity
Many definitions, in one way or the other, make use of the 3 V’s of big data, which are: Volume, Variety, and Velocity.
Basically, we can define Big Data, as the processes or solutions that allow us to aggregate, transform, and analyze huge amounts of data, that is being produced very fast, and respond to a variety of data types and structures.
The data can be tweets, comments, Facebook posts, reviews, real-time geographic locations of incidents, resumes or other documents uploaded to a website.
These processes aim to generate valuable insights from that data to drive business decisions.
© 2013 Computer Technology Solutions, Inc.

11. Big Data technologies © 2013 Computer Technology Solutions, Inc.
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Big Data technologies
There are countless technologies and platforms in the world of Big Data. They focus on the storage and processing of the data. They strive for high scalability, using distributed, cloud-based or in-memory processing.
Hadoop is at the core of those technologies, offering an ecosystem of solutions from HDFS for the storage of the data, to processing the data with MapReduce, Hive, Spark, Solr and others.
There are also NoSQL databases like Hbase and Cassandra in the Hadoop ecosystem, as well as the popular MongoDB.
Cloudera, Hortonworks and Mapr are distributions of Hadoop.
Microsoft Azure and Amazon Web Services are cloud storage and distributed platforms powering BigData and other solutions.
----
Hadoop Distributed File System (HDFS) HDFS is a scalable, fault-tolerant Java based distributed file system that is used for storing large volumes of data in inexpensive commodity hardware
Microsoft Azure: cloud computing platform offered by Microsoft
Amazon Web Services: is the cloud base scalable and distributed system offered by Amazon
Hadoop MapReduce: framework for distributed processing of data
Hive: data warehouse infrastructure on top of Hadoop, for query, summarization and analysis in a SQL-like language.
Hbase: NoSql database., providing real-time read/write access to large datasets with extremely low latency as well as fault tolerance.
Cassandra: NoSQL database, which is highly scalable, fault tolerant and can be used to manage huge volumes of data
Solr is the open source platform for searches of data stored in HDFS in Hadoop. Solr enables powerful full-text search and near real-time indexing
Spark: cluster computing framework for large-scale data processing.
MongoDB: NoSQL database, document oriented with high scalability. Stores JSON like documents with dynamic schemas
Cloudera, Hortonworks and MapR are Hadoop distribution platforms
© 2013 Computer Technology Solutions, Inc.

12. Modern BI and Analytics
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Modern BI and Analytics
$16.9 billion global revenue in 2016
IT-led reporting and analytics platform
business-led
self-service analytics
The Business Intelligence and Analytics market is forecast to reach 16.9 Billion in global revenue this year, according to Gartner, Inc.
There is a huge demand for analytics and insights. Business executives are relying on data to drive their decisions more than ever.
Furthermore, there are many companies building products out of their BI solutions. They are no longer using BI processes to make better decisions for their businesses, they are using their BI solutions as a new product or service, offering their clients a competitive advantage.
STORY! Provide example of my previous company and their dynamic data warehouse environment. Mention how they use Data, BI, and Analytics as a Product itself.
However, the traditional reporting and analytics platform, where the IT staff produce the reports and ad-hoc analysis is transitioning to a modern BI and analytics platform where business users has self-service tools to explore, aggregate, and analyze the data on demand.
[Explain more about this transition.]
Clients don’t want reports anymore, they want IT to provide the data, and they have their own tools.
STORY! Provide example of our current EDW engagement at CTS
--More info at:
© 2013 Computer Technology Solutions, Inc.

13. Traditional BI vs Modern BI
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Traditional BI vs Modern BI
Traditional BI
Modern BI
Source Data & Preparation
IT-built dimensional models / DW loaded with ETL processes
Upfront modeling and preparation not required
Analytics
Structured reporting via pre-defined reports or ad-hoc requests
Free-form exploration of the data
Creation
IT staff
Business users
Key Benefit
Governance of data, ensuring a single version of the truth
Flexibility and timely access to data insights
Can we blend both?
Explain key differences between traditional and modern BI
Can we blend both?
We sure CAN. Explain why.
© 2013 Computer Technology Solutions, Inc.

14. Modern BI and Analytics
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Modern BI and Analytics
Self-service
Mobile analytics
Cloud-based
BI & Analytics
Predictive analytics
Advanced visualizations
Big Data
Modern BI and analytics platforms leverage the cloud, as well as columnar and in-memory storage increasing the scalability and processing speeds to incredible levels.
New platforms provide mobile first experience and self-service capabilities, offering access to the information from all devices, and without predefined structures.
Business users have their insights when they need them!
Big data, predictive analytics, and the internet of things enhance traditional BI solutions to a new level.
More info at: using:
© 2013 Computer Technology Solutions, Inc.

15. Advanced visualizations
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Advanced visualizations
Visualizations have evolved from thousands of rows in a spreadsheet, to advanced dashboards with interactive maps, word cloud, gauge charts, scatter and bubble charts.
© 2013 Computer Technology Solutions, Inc.

16. BI Evolution is Critical
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BI Evolution is Critical
How important is data warehouse modernization?
Is your data warehouse relevant?
Is your data warehouse evolving?
There is a great research published this year by TDWI named “Data Warehouse Modernization: in the Age of Big Data Analytics”.
I encourage you to check them out, and I included their link to this presentation.
Describe the results of those 3 questions.
A Business Intelligence solution, the data warehouse, or any analytics platform HAS TO EVOLVE. It is critical for every organization, no matter their size, industry, or budget.
BI solutions needs to stay relevant and updated to help the business achieve its goals.
Any good BI solution is a dynamic project, expanding and adapting to the new conditions
STORY! TDWI name
From: The Data Warehousing Institute
To: Transforming Data With Intelligence
More info at:
research report from TDWI.org
© 2013 Computer Technology Solutions, Inc.

17. Takeaways? © 2013 Computer Technology Solutions, Inc.
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Takeaways?
Ask the audience! “What do you take away from this presentation?”
© 2013 Computer Technology Solutions, Inc.

18. Takeaways Exciting moment for BI, Big Data, and Analytics
Printed on 1/27/2018
Takeaways
Exciting moment for BI, Big Data, and Analytics
Requirements
Technology
BI Solutions
YOU have to EVOLVE
Evolution
Ask the audience! “What do you take away from this presentation?”
My take away, and what I want to make sure they get from this presentation:
It is a very exciting moment for a career in Business Intelligence, Data Warehousing, and Analytics.
There are TONS of opportunities to learn, build expertise, and help your clients or employers.
-User Requirements evolve, which means that the problem changes
-Technology evolves in the quest to solve those new problems
-BI solutions needs to evolve
Therefore, in order to be successful, you need to be willing to evolve along with the problems, technologies and solutions
 You need to keep a GROWTH MINDSET
STORY! Most important piece of advice: Don’t learn tools, learn the concepts and how the tool solve the problem.
© 2013 Computer Technology Solutions, Inc.

19. Questions © 2013 Computer Technology Solutions, Inc.
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Questions
Questions?
Open the discussion for any question from the audience
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20. Printed on 1/27/2018
References
Business Intelligence and Analytics – MIS Quarterly research
Think of Big Data as Accelerated, Enhanced Data – askcts.com
Big Data Stack: Tools and Technologies – edgeOfTesting.com
Gartner Says Worldwide Business Intelligence and Analytics Market to Reach $16.9 Billion in 2016 – gartner.com
10 Business Intelligence Trends for 2016 – pcmag.com
Data Warehouse Modernization – tdwi.org
Images: search, terminology, takeaways and questions – freepik.com
Other references
- Business Intelligence ( – olap.com
- Business Intelligence ( – tdwi.org
- Microsoft BI Stack Architecture ( –pospic.com
© 2013 Computer Technology Solutions, Inc.

21. Thank you! https://qr.net/Kbx3J8
Printed on 1/27/2018
Thank you!
Yissel Espinosa Cervantes
Consultant
@YisselEspinosa
Thank you!
End presentation thanking the audience for the opportunity and their participation.
Encourage them to provide feedback at the URL / QR Code on the screen
(Give printed copies of this slide, if possible)
Remind them about contact information. “Please, reach out any time. I would love to help you out.”.
© 2013 Computer Technology Solutions, Inc.

22. Thank you! https://qr.net/Kbx3J8 Yissel Espinosa Cervantes Consultant
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Thank you!
Yissel Espinosa Cervantes
Consultant
@YisselEspinosa
Slide to print, with bigger contact info
© 2013 Computer Technology Solutions, Inc.