Last seats left for Business Analytics 360 - 18th Nov and Data Science using Python batches - 18th Nov in Delhi-NCR
 

Business Analytics Course - Business Analytics 360!

Power-packed Business Analytics course for beginners who want start their career in Analytics & Data Science!

This business analytics training is for beginners who want to start from basics of Excel, SQL, Tableau moving to advanced tools like SAS, Python data science, including machine learning. Evolved from our most popular course SAS + Business Analytics training, this is the best  business analytics course in India curated for candidates who are looking for job oriented business analytics certification but have no prior knowledge of any business intelligence or data analytics tools. Most extensive business analytics course in Bangalore and Delhi NCR, with flexibility of also attending the live online training and self-paced video based mode as well. 


However, learning tools without techniques is half the job done in today's Analytics world. So to help candidates emerge as 'Industry Ready' professional, this Business Analytics course in Indida encompasses basic statistical concepts to advanced analytics and predictive modelling techniques, along with machine learning, using most widely used analytics tools, like Excel, Tableau, Python, SAS (including Proc SQL). This analytics certification course is for all those aspirants who want to switch into the field of data science and begin their career as business analyst.


One of the best Business Analytics online course in India and is also available in Delhi NCR and Banaglore, with aim to provide you job oriented Data Science and Business Analytics skills.


Business Analytics training 'Business Analytics 360' Duration: 415 hours (At least 144 hours live training + 30 hours video based module + around 10 hrs of weekly self-study and practice)

Who Should do this course?

Beginner candidates from various quantitative backgrounds, like Engineering, Finance, Maths, Business Management who are looking for Business Analytics training to start their career in the field of Analytics and Data Science.

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Course Duration 415 hours
Classes 50
Tools Excel, VBA, Tableau, SAS, Python
Learning Mode Live/Video Based
Next Batch18th November, 2018 (Gurgaon)

Introduction to Excel

  • Introduction to Excel Environment
  • Explanation about data calculation in Excel
  • Use of Shortcuts
  • Formatting and Conditional Formatting
  • Working with Formulas - Logical and Text Functions
  • Understanding about Sorting, Filtering and Data Validation
  • Data Analysis using Pivot Tables

Introduction to Charts and Functions

  • Understaing of Mathematical, Statistical Functions
  • Worksheet and Workbook Protection and Security
  • Understanding of Name Ranges
  • Introduction of Charts
  • Introduction of Form Controls
  • Understanding of Data Tools Panel

Dashboard Designing

  • Overview of Dashboards
  • Deciding on Dahsboards
  • Trends and Scenarios using charts
  • Advanced Charting Techniques using Thermometer, Doughnut, Pareto, Panel and Step Chart
  • Designing Sample Dashboard using Form Controls
  • Tips and Tricks to enhance dashboard designing

SQL- SQL Server

  • Data manipulation (DML Commands)
    • Insert, Update & Delete statements
    • Select statement – Where, Group By, Order by & Having clauses
  • Utilizing the Object Explorer
  • Introduction to SQL Server Management Studio
  • Understanding basic database concepts
  • Getting started
  • What is SQL – A Quick Introduction
  • Understanding basic RDBMS concepts
    • Schema –Meta Data –ER Diagram
    • Looking at an example Database design
    • Data Integrity Constraints & types of Relationships (Primary and foreign key)
    • Basic concepts – Queries, Data types & NULL Values, Operators and Comments in SQL
    • Data based objects creation (DDL Commands)
    • Creating, Modifying & Deleting Tables
    • Drop & Truncate statements – Uses & Differences
    • Alter Table & alter Column statements
  • Working with Select statement
    • Union and Union All – Use & constraints
    • Intersect and Except statements
    • Joins & Aliases
    • Accessing data from Multiple Tables
    • Inline and sub-queries
    • SQL Functions – Number, Text, Date, etc
    • SQL Keywords – Top, Distinct, Null, etc
    • SQL Operators, Use of wildcards, etc
  • Optimizing your work
    • Sub-queries vs. Temp Tables vs. Joins
    • Optimizing for Composite keys & Non-numeric Primary keys

Tableau: Getting started with Tableau

  • What is Tableau? What does the Tableau product suite comprise of? How Does Tableau Work?
  • Tableau Architecture
  • What is My Tableau Repository?
  • Connecting to Data & Introduction to data source concepts
  • Understanding the Tableau workspace
  • Dimensions and Measures
  • Data Types & Default Properties
  • Tour of Shelves & Marks Card
  • Using Show Me!
  • Building basic views
  • Saving and Sharing your work-overview

Tableau: Building Views (Reports) – Basics

  • Date Aggregations and Date parts
  • Cross tab & Tabular charts
  • Totals & Subtotals
  • Bar Charts & Stacked Bars
  • Line Graphs with Date & Without Date
  • Tree maps
  • Scatter Plots
  • Individual Axes, Blended Axes, Dual Axes & Combination chart
  • Edit axis
  • Parts of Views
  • Sorting
  • Trend lines
  • Reference Lines
  • Forecasting
  • Filters
  • Context filters
  • Sets
    • In/Out Sets
    • Combined Sets
  • Grouping
  • Bins/Histograms
  • Drilling up/down – drill through
    • Hierarchies
    • View data
    • Actions (across sheets)

Tableau: Building Views (Reports) – Advanced Maps

  • Explain latitude and longitude
  • Default location/Edit locations
  • Symbol Map & Filled Map
  • Custom Geo Coding

Tableau: Calculated Fields

  • Working with aggregate versus disaggregate data
  • Explain - #Number of Rows
  • Basic Functions (String, Date, Numbers etc)
  • Usage of Logical conditions

Tableau: Table calculations

  • Explain scope and direction
  • Percent of Total, Running / Cumulative calculations

Tableau: Parameters

  • Create What-If analysis
  • Using Parameters in
    • Calculated fields
    • Bins
    • Reference Lines
    • Filters/Sets
  • Display Options (Dynamic Dimension/Measure Selection)

Tableau: Building Interactive Dashboards- (Building & Customizing)

  • Combining multiple visualizations into a dashboard (overview)
  • Making your worksheet interactive by using actions
    • Filter
    • URL
    • Highlight

Tableau: Working with Data

  • Multiple Table Join
  • Data Blending
  • Difference between joining and blending data, and when we should do each
  • Working with the Data Engine / Extracts
  • Toggle between to Direct Connection and Extracts

Introduction to the Analytics world and SAS role

Analytics World

  • Introduction to Analytics
  • ETL CONCEPT and role of SAS in ETL
  • SAS in advanced analytics
  • SAS Certification: Induction and walk through

Getting Started with SAS

  • SAS software installation
  • Introduction to SAS, GUI
  • Different components of SAS language
  • All SAS programming windows
  • Concept of SAS Libraries and Creating Libraries
  • Variable Attributes - (Name, Type, Length, Format, In format, Label)
  • Importing Data and Entering data manually

Understanding Datasets

  • Descriptor Portion of a Dataset (Proc Contents)
  • Data Portion of a SAS Dataset
  • Variable Names and Values
  • SAS Data Libraries

SAS: Accessing the Data

Understanding Data Step processing

  • Data Step and Proc Step
  • Data step execution
  • Compilation and execution phase
  • Input buffer and concept of PDV

Importing Raw Data files

  • Column Input and List Input and Formatted methods
  • Delimiters, Reading missing and non standard values
  • Reading one to many and many to one records
  • Reading Hierarchical files
  • Creating raw data files and put statement
  • Formats / Informat

Importing and Exporting Data (Fixed Format / Delimited)

  • Import Wizard
  • Proc Import / Delimited text files
  • Proc Export / Exporting Data from SAS
  • Datalines / Cards
  • Atypical importing cases (mixing different style of inputs)
    • Reading Multiple Records per Observation
    • Reading “Mixed Record Types”
    • Sub-setting from a Raw Data File
    • Multiple Observations per Record
    • Reading Hierarchical Files
  • Importing Tips

SAS: Data Understanding, Managing and Manipulation

Understanding and Exporing Data

  • Introduction to basic Procedures - Proc Contents, Proc Print
  • Operators and Operands
  • Conditional Statements (Where, If, If then Else, If then Do and select when)
  • Difference between WHERE and IF statements and limitation of WHERE statements
  • SAS Labels, Commenting
  • SAS System Options (OBS, FSTOBS, NOOBS etc…)

Data Manipulation

  • Proc Sort - with options / De-Duping
  • Accumulator variable and By-Group processing
  • Explicit Output Statements
  • Nesting Do loops
  • Do While and Do Until Statement
  • Array elements and Range

Combining Datasets (Appending and Merging)

  • Concatenation
  • Interleaving
  • Proc Append
  • One To One Merging
  • Match Merging
  • IN = Controlling SAS merge and Indicator

SAS: Functions

  • General form of SAS Functions
  • Arithmetic Functions
  • Date and Time Functions
  • Text Manipulation Functions
  • Nested Functions

SAS: Data Analysis and Reporting

  • Proc Freq
  • Proc Format for user defined formats
  • Proc Means
  • Proc Summary
  • Proc tabulate
  • Proc report
  • Concept of the Output Delivery System
  • Using ODS Statements to save data on external destination

Advance SAS - Data Mining with Proc SQL

  • Introduction to Proc SQL
  • Basics of General SQL language
  • Creating table and Inserting Values
  • Retrieve & Summarize data
  • Group, Sort & Filter
  • Using Joins (Full, Inner, Left, Right and Outer)
  • Reporting and summary analysis
  • Concept of Indexes and creating Indexes (simple and composite)
  • Connecting SAS to external Databases
  • Implicit and Explicit pass through methods

Advanced SAS - SAS Macros

  • Global and Local Variables
  • Macro Parameters and Variables
  • Different types of Macro Creation
  • Defining and calling a macro
  • Using call Symput and Symget
  • Macros options (mprint symbolgen mlogic merror serror)

Working smartly with SAS

Debugging SAS

  • How to read log file efficiently
  • Tips to debug code

Efficient SAS Programming

  • Code optimization and Efficient SAS Programming Techniques
  • Saving CPU Time, I/ O processing time
  • Disk Space Saving Measures
  • Memory saving tips

MS-VBA (video-based)

  • Working with VBE (Visual Basic Editor)
  • Introduction to Excel Object Model
  • Understanding of Sub and Function Procedures
  • Key Component of Programming Language
  • Understaing of If, Select Case, With End With Statements
  • Looping with VBA
  • User Defined Function
  • Some Commonly Used Macro Examples
  • Error Handling
  • Object and Memory Management in VBA
  • User Form Controls
  • ActiveX Controls
  • Communicating with Database MS Access through ADO - Exporting/Importing Data

Introduction to Data Science with Python

  • What is analytics?
  • Analytics vs. Data warehousing, OLAP, MIS Reporting
  • Relevance in industry and need of the hour
  • Types of problems and business objectives in various industries
  • How leading companies are harnessing the power of analytics?
  • Critical success drivers
  • Future of analytics and critical requirement
  • Different phases of a typical Analytics projects

Python Foundation

  • Python Essentials (Core)
  • Operations with NumPy (Numerical Python)
  • Overview of Pandas
  • Accessing/Importing and Exporting Data using python modules
  • Cleansing Data with Python
  • Data Analysis – Visualization using Python
  • Basic statistics & implementation of stats methods in Python

Python: Machine Learning

  • Introduction to Machine Learning & AI
  • ML Concepts – Learning algorithms
  • Supervised Learning – Regression problems using Linear Regression
  • Supervised Learning: Classification Problems using Logistic Regression
  • Supervised Learning: Classification & Regression Problems using Decision Trees
  • Supervised Learning: Classification & Regression Problems using Ensemble Learning
  • Supervised Learning: Classification & Regression Problems using KNN
  • Supervised Learning: Classification & Regression Problems using Bayesian Techniques
  • Supervised Learning: Regression & Classification problems using Support Vector Machines
  • UnSupervised Learning: Segmentation problems using Cluster analysis
  • UnSupervised Learning: Segmentation problems using Cluster analysis
  • Supervised Learning: Forecasting problems using Time Series Analysis
  • Forecasting overview
  • Basics of Time Series
  • Supervised Learning: Forecasting problems using Time Series Analysis
    • Stationary Time Series Methods
    • Trend Based Time Series
    • Seasonal Time Series
    • Advanced Techniques
    • Evaluation of Forecasting
  • Supervised Learning: Regression & Classification problems using Neural Networks

Python: Text Mining NLP/NLG

  • Introduction to Text Mining
  • Text Processing using Base Python & Pandas, Regular Expressions
  • Text Processing with specialized modules like NLTK, sklearn etc
  • Initial data processing and simple statistical tools
  • Advanced data processing and visualization

Python: Final Projects

  • Sentiment Analysis (Classification, weighted score etc)
  • Word cloud analysis (Examples)
  • Segmentation using K-Means/Hierarchical Clustering (Grouping the similar words)
  • Classification (Spam/Not spam)
  • Topic Modeling (LDA, LSA, Louvain etc)
  • Text Summarization

"Being a graduate from Commerce stream i was very skeptical about switching my field to analytics. There were a lot of questions that I had in my mind regarding future job prospects. All my questions were answered by Mr. Sumeet Bansal and he showed me the correct path for my future. If you wish to start your career in analytics then Alabs is the perfect choice as the faculty of Alabs have deep industry experience and currently working in the Analytics fields, they share examples with us which they face in their day to day life. The best part about the counsellors of Alabs is that they never try to sell their courses instead they would only suggest what is right for your future. Special thanks to Ankur for teaching SAS in such a way that being from a non technical background still i was able to understand the language. He will keep you engaged in the class even if you are attending the session online.The assignments and projects are very effective and it helps a lot while facing interviews I would like to mention that Alabs will be there to teach you and make you industry ready, however, the effort has to come from your side. There might be a time when you might feel that you are stuck, just stay focussed and you will do wonders. Patience is the key. Lastly I'd like to thank the whole team of Alabs for providing constant support and looking forward to join another course from your institute."


Chaitanya Relan
(Manager, American Express)

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