Female Student

Analytics & BI Engineering

Learn key technologies and techniques, including Business Intelligence and Analytics Engineer, to analysis large-scale data sets to uncover valuable business information

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There is one session available

Start September 30

This Program is part of Applied Data Science & ML Engineering

Application is free, only pay if you want to enroll

About this Program

This is an introductory program for freshers / beginners / non-technical folks who want to take a sneak peek into the working of a Business Intelligence & Analytics engineer project and understand different career options and associated responsibilities for the same. This program is about how a BI project is executed, what are the different layers of a BI architecture, and which career track one can choose to work on based on your areas of interest in a BI project. This program is not meant to be a exhaustive reference of each and every tool and technology available in the Business Intelligence field. 

1

FUNDAMENTALS OF ANALYTICS
 

2

MASTERING IN PYTHON
 

3

STANDARD SQL

 

4

BUILDING MODERN DATA WAREHOUSE BUILDING IN BQ

5

REAL-TIME DASHBOARD AND BI FUNCTIONS

6

CAPSTONE PROJECT

 

Who can take this course?

BI & Analytics Engineer course is perfect for professionals who work with data and want to learn more about business intelligence. This course covers core concepts in the field and is a stepping-stone onto more advanced Business Intelligence and data analytics topics.

 

Common career paths for students who take the program are Business Intelligence, Asset Management, Data Analyst, Quantitative Analyst, and other finance careers.

Length

8 Weeks

Effort

10–15 hours per week

Price

BDT 21,000
(Before offer BDT 30,000)

Instruction

Real-time

Eligibility

University level education

Level:

Beginner to Advanced
 

Language

English (Primary), Bengali

Instructors From World Class Industries and Academic institutions

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JUWEL RANA, PHD

Global Analytics Leader, Norway

Helping industry to simplify analytical needs by developing robust highly scalable analytical products

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Dr. SRH Noori

Associate Head at DIU, Bangladesh

Journey from Industry to Academy. Acting as the bridge between the industry and academia.

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Seraj Al Mahmud Mostafa

Data Scientist at Montana State University, USA

Passionate to optimising performance from Data Journey from Industry to Academy. Acting as the bridge between the industry and academia.

Content Blocks of VBA's BI & Analytics Engineer Program

Fundamentals of analytics

  • Understanding analytics processes
  • Knowing about important roles and responsibilities as
    • data scientists
    • data engineers
    • business analysts
    • market analysts
    • research scientists
    • analytics engineers and so on
  • Developing foundation around
    • Analytics platform
    • business intelligence platform
    • AI platform
    • Data platform
  • Understanding End to  end perspective of Data Product
  • Cross industry  alignment of analytical use cases such as
    • Telco,
    • Retail
    • Information Technology
    • Finance and Banking
  • Modern data science professionals way of working
    • Cross functional team​
    • Agile principles
  • Importance of capacity building in  Taking End to end responsibilities of developing data products
  • Data professionals proposition in both the global and local market
Investment Chart
 
 

Mastering in python

  • Know how to use Python Environment (week 1)
  • Know how to use Anaconda
  • Google colab for Python programming (week 1)
  • Introduction to Python 3 basics (week 1)
  • Understand Python script structure Know variables, naming, types, and operators (week 1)
  • Know strings, formatting, print (week 1)
  • Understand list, tuple, set, frozen set, dictionary (week 2)
  • Understand List comprehension (week 2)
  • Understand Dictionary comprehension (week 3)
  • Understand Control Structures: IF -Else, Loops (week 3)
  • Introduction to PANDA (week 4)
  • Importing dataset, creating data frame (week 4)
  • Know how to use Pandas in Data manipulation and analysis Understand Pandas Series and Data frames (week 4)
  • Know all on how to use NumPy and NumPy Arrays (week 5)
  • Understand Lambda function (week 5)
  • Understand the concept of Object in Python (week 5)
  • Know file manipulation/scripting (week 6)
  • Know error handling (week 6)
  • Know how to use Databases with Python (week 6)
Coding Station

STANDARD SQL &
BUILDING MODERN DATAWAREHOUSE INBQ

  • What is SQL?
  • Data Model - Understanding Data
  • Data Model - History of Data Model
  • Hierarchical, Network, Relational, Entity, Relational Semantic, NoSql
  • Data Model  - Relational Vs Transactional Model
  • SQL Statement Type
  • DML - Data Manipulation Language
  • DDL - Data Definition Language
  • DCL - Data Control Language
  • TCL - Transaction Control Language
  • Create Table, Physical Table, Temporary Table, Intermediary Table 
  • Table Vs Views
  • Adding Comments & Best Practices on coding
  • Retrieving Data with Select
  • Data Types
  • Filtering data with Where
  • Distinct and Case
  • Aggregate Functions
  • Count, SUM, Min, Max, Null & Data Type Handling
  • Filtering aggregate data with Having
  • Join Basics - 6 types of join, Inner Join, Right Join, Left Join, Full Join
  • Sub/Nested Queries
  • Window Ranking & Aggregation
  • Pivot & UnPivot
  • Large Complex Queries
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Real time dashboard and end to end business intelligence functions

  • Know the basics of DataStudio
  • Know how to connect Data Source
  • Ex. Google Marketing Platform products, including Google Ads, Analytics, Display & Video 360, Search Ads 360
  • Google consumer products, such as Sheets, YouTube, and Search Console
  • Databases, including BigQuery, MySQL, and PostgreSQL
  • Flat files via CSV file upload and Google Cloud Storage
  • Social media platforms such as Facebook, Reddit, and Twitter
  • In total Know how to import data from different sources to Data Studio
  • Know how to transform in Datastudio
  • Know how to create Reports in DataStudio
  • Tell your data story with charts, including line, bar, and pie charts, geo maps, area and bubble graphs, paginated data tables, pivot tables, and more.
  • Make your reports interactive with viewer filters and date range controls. The data control turns any report into a flexible template report that anyone can use to see their own data.
  • Include links and clickable images to create product catalogs, video libraries, and other hyperlinked content.
  • Annotate and brand your reports with text and images.
  • Apply styles and color themes that make your data stories works of data visualization art.
  • In total Understand how to use and modify Visualizations in Reports
  • Know how to create Dashboard in DataStudio 
  • Understand Data Studio Security
  • Know how to create Analysis Services Database with Datastudio
  • Know how to use Analysis Services with Datastudio
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Capstone project building end-to-end data product industry level product development

  • End-to-end data science project development
    Industry focused project implementation using relevant domain specific dataset
  • Implementation:
     
    Value Base Academy will offer capstone projects on four demanding areas as stated in the following from A to D. Students are free to select their own domain for the capstone project upon consultation with relevant instructors.
     
     
    ​​Project A: Telecom
     
    Project B: Sales & Marketing
     
    Project C: Information Technology
     
    Project D: Fintech, Finance and Marketing
     
    Project E: Retail
     
    Project F: Health Care
     
    Project H: Media and Digital Marketing Agencies
    Project I: Garments and Textile Industries
Financial Report