FINAL BLOG

Wow These eight weeks flew by so fast! This was one of the most relevant and interesting courses I have taken so far. From articulating the characteristics of big data to analyzing networks and how it can be used as a tool for business analytics we have learned so many tools, concepts and techniques that are already helping me to gain a better understanding of businesses and how data analysis can or could be used as a tool in my work life as well as my passion projects. Let’s dive into all that we learned in our class in each module.

Module 0: Introduction to business analytics

In this module we learned what big data is, before this I wasn’t aware how ‘BIG’ big data actually is. We looked at the various sources of big data and the paradigm shift that it is causing today.

These paradigm shifts include the ‘datafication’ of the world, rich in semantics and highly dynamic content and “N = ALL” with billions of users and massive traces of human activities

We further explored the problems that come with big data and the V’s of big data: volume, velocity and variety. Reading my fellow classmates articles and blogs I learned about two more V’s which are value and veracity. 

          

                                             Source: https://morioh.com/p/ca19c6b8c0fe

For the problems listed above, we learned about business intelligence. What it is, the architecture (old and new), the activities involved in BI, the BI lifecycle, and its various applications.

There were so many articles that week that helped me learn so many different applications of BI. One that really stuck with me was how BI is used to optimize energy usage by using devices like smart meters, help- is being delivered in drought ridden areas and it also helps in cutting down illegal watering. In CA these efforts helped homeowners cut down their water usage by 80%. (https://datafloq.com/read/7-unusual-uses-of-big-data/)

In my company we use BI for predicting which areas will be overbooked around specific times (owing to festivals, concerts, games, storms, etc) using our historical data dump and so now we are able to prepare, book, displace and plan ahead of these events ensuring that our services have the least impact of these events.

 

Module 1: Data Warehouse Design and Implementation

In this module we learned about the Data Warehouse design cycle, balanced scorecard, and dimensional modeling star schema design. From understanding the types of information assets (OLTP and OLAP), differences between data warehouse and data marts and the processes involved in data warehouse design, we explored all of it. Understanding this actually helped me have a better understanding of the database and structure we use in my company. This also helped me explain the processes, how our code works and what it is trying to achieve to my team more effectively. It is surprising how developers can fill in the blanks the managers and end users tend to forget once we have a clear understanding of how the data is stored, its relationships and the end goal.

In this module we also learned about performance management and balanced scorecard. The need to create and understand key performance indicators (KPIs) and metrics, followed by a case study of southwest airline and how they used a balanced scorecard to maintain their profits in a time when all other airlines in the industry struggled to do so. It was so interesting for me because of I work closely with the airline industry, but I never had the opportunity to learn their metrics, issues and processes. The Southwest case study really helped me strengthen my understanding of how a balanced scorecard can be used to measure, plan and improve an organizations performance.

This module also taught me about dimensional modeling, star schema decision, snowflake schema design, data cube and its operations. In week 2 of our module we learned the concepts of advanced star schema design and data quality analysis, which is a very important step in data warehouse designing process. We looked at the various techniques and the software tools available in the market today like DQ analyzer that makes the process of data cleaning easier and automates the analysis involved in improving data quality as well saving data scientists a lot of time and effort that goes into this tedious task. The assignment where we had to design a star schema helped me understand and cement in the modules learning.

In the last week of the module, we learned about dashboard design and its use for analytics. We worked with tableau to create a dashboard to view the important data at glance for a dataset which had data for bird strike incidents and their effects on airplanes. This segment was a class favorite and was mine too! I actually got to learn tableau which is something we use in one of our products and my boss really loved the dashboard designed for the assignment. The airline theme linking so well with my job was like a cherry on the top! It really helped me learn the nuances of data visualization and analytics to aid better visibility and smarter decision making.

Module 2: Web Analysis

In this module we learned about web analysis, web analytics cycle, the five Ws of web analytics, the types of web traffic, the various web metrics and the KPIs involved in web analytics. The five W’s of web analytics: what, who, when, and why; help us understand the visitor behavior, the types of web traffic help us understand the sources of visitors, the web metrics help us measure the website usage, and the KPIs of web analytics help us measure and understand how well are we achieving our desired goals.

Source: https://engaiodigital.com/what-is-web-analytics/

In this module we also learned how to use google analytics. Before this module I had no idea about the amount of useful information ranging from user demographic to sources of traffic can be captured by web analytics tools. I can’t wait to implement this in our company’s web products or just use it in my passion projects. The articles I found for this module really aided my understanding of web analytics and the benefits of using google analytics. I pitched the project idea of using google analytics in our companies products to our bosses and due to the various benefits of Google analytics that I learned I was able to pitch this idea with good arguments and now it is up for review this month!

source: https://engaiodigital.com/google-analytics/

Module 3: Social media analytics/network analysis

In this module we learned about networks, what they are, their components, their types, their visualizations and analytics. After looking at and understanding the various concepts of networks, we dove deeper into information and network visualizations. Information visualization can be useful for exploring datasets, for communicating ideas that emerge from these datasets and to understand the data and take action on it. Applying this to networks, visualizing a network can reveal various important information. It can help us understand the communities, the actors in the network, their interactions, where they occur, how information flows through the network etc.

The different types of network layouts help us exploring our network in different ways. They are, force directed, geographical, circular, clustering, and hierarchical. We also saw how LinkedIn had functionalities to visualize your network and we looked at a few examples for the same. Then we looked at the various network properties that help us understand and quantify the nodes and networks behavior. Under this module we learned to use Gephi which is a network visualization and analysis tool. We also worked on an assignment that visualizes the twitter network of fortune 500 companies and their interaction. From the various articles I read, there were such fascinating uses of network analysis, social network analysis and I also learned about organizational network analysis. There were so many interesting uses of network analysis but the one that stuck with me was how twitter used network analysis to identify and take down propaganda bots in their networks.

 To summarize, I have learned so much from this class and it has already been helping me understand the bigger picture and purposes of tasks that are generated in my work life. The articles from the lectures and the ones of my classmates have helped me learn real life examples and implementations of our study material. The blogs have helped me better understand concepts that I missed or was confused with after the lecture; And the one I’m most thankful for is that I have learned how to work with relevant tools and skillsets that I cant wait to cultivate and utilize to help make smarter business decisions. In today’s modern data driven era, with new and sophisticated concepts being continuously developed in big data and BI, ranging from evolving architecture, algorithms, software to optimization processes; I believe, if you are not utilizing them you are definitely missing out on the invaluable insights, competitive leverage and capabilities that business intelligence can equip your business with.