A picture is worth a thousand words ! Data Analytics VS Web Analytics VS Business Intelligence VS Big Data. Why Data is important in Marketing ?

1. A picture is worth a thousand words !
Masum Billah
Data Scientist

2. What is Analytics > Data Analytics
• A method of analysing data to find patterns, trends, relation, correlation,
answer, questions, problem, solution and so on
• Types of Data Analytics
• Descriptive analytics
• Diagnostic analytics
• Predictive analytics
• Prescriptive analytics
Data Analytics VS Web Analytics VS Business
Intelligence VS Big Data

3. Types of Data Analytics
• Descriptive analytics - This method needs the collection of relevant data,
processing of the data, data analysis and data visualization. This process
provides essential insight into past performance. Like staff KPI, (ROI return on
investment) and so on.
• Diagnostic analytics: - It helps answer questions about why things happened.
They take the findings from descriptive analytics and dig deeper to find the
cause and discover why they got better or worse. There are lots of statistical
analysis involve
• Predictive analytics: - These techniques use historical data to identify trends
and determine if they are likely to recur and helps us to learn what may happen
in the future with different level of confidence. Experts use wide range of
mathematical, statistical and machine learning techniques, such as: neural
networks, decision trees, and regression, ensemble learning and so on.
• Prescriptive analytics: - Here input comes from PA and use that to find the
answer for what should be done. Which helps industries to make decisions in
the face of uncertainty. Machine learning is being used to do Prescriptive
analytics.

4. As a Data Scientist I prefer to work this way
1) Data wrangling
2) EDA (Exploratory data analysis)
3) Prepare Data for ML (Machine learning)
4) ML Model
• Supervised learning
• Unsupervised learning
• Predictive Model
• Deep learning
• AI Model

5. Web Analytics
• Combination of technique and technology help business to record
visitors’ online behaviours and activities on your website.
• Web Traffic: The number of incoming and outgoing website visitors
you receive within a given time-period
• Views and click:- The number of times a page has been viewed and
clicked
• New visitors: First-time visitors to your website within a given time-
period
• Conversion rate: The rate of visitors making purchases from your
site, signing up for newsletters or subscribing to a service
• Organic traffic: Visitors that arrive at your website directly from a
search engine and not from social media or other blogs
• Direct traffic: Visitors that come to your website by going to your
address directly and not from a search engine
• Some popular Tools:- Google Analytics, Mint, Clicktale, CrazyEgg

6. Business Intelligence
• Business Intelligence has a direct impact on organization, is
a collection of strategies and technologies that are used to
understand how organizations work and make better data-
driven decisions.
• Popular BI tools: - Microsoft Power BI, Tableau, Micro
Strategy, SAS, Oracle BI, IBM Cognos Analytics and so on.
• Those Business Intelligence tools perform data analysis and
create reports, dashboards, maps, graphs, and charts to
give users with detailed intelligence about the nature of the
business.

7. Big Data

8. Big Data

9. Big Data
• Big data is a buzzword nowadays, this term used to describe the large
volume of structured and unstructured data.
• Three Vs in Big Data “volume velocity variety”
• Ø Volume refers to the amount of a specific dataset/database.
• Ø Variety refers to the number of types of data in a specific Dataset. As we
know structured and / relational database. When we talk about Big Data,
we are talking about structure, unstructured and types of data. For
Example, picture, number, string, character, text, audio, video and so on
these types of data require extra power of preprocessing to derive meaning.
• Ø Velocity refers to the speed / fast data increasing and processing
scenario. Usually, the highest velocity of data streams directly into memory
versus being written to disk.
• Some Big Data buzzword :- Apache Hadoop, HDFS (Hadoop Distributed File
System), Spark, PySpark, Apache Hive ….

10. Why Data is important in Marketing
• Market validation
• Learn about your customer
• Find a problem that customer face
• Customer sentiment Analysis
• MBA (Market Basket Analysis)
• Offer a solution not product
• Data Driven NonTech Business
• Uber – user share data point A to B
• Airbnb
• Online shopping

11. Invespcro

15. Thank you very much  .
If you have any query, please let me know.
LinkedIn :-https://www.linkedin.com/in/masumdatascientist/
Website :- www.aindatalab.com
Masum Billah
Data Scientist