Using IESVE for Loads, Sizing and Heat Pump Modeling to Achieve Decarbonization
Bi reporting and data analysis training Contents
1. BI reporting and Data
Analysis Training
DV Analytics Training Institute
dvanalytics.training@gmail.com
http://dvanalyticstraininginstitute.blogspot.in
https://www.facebook.com/DvAnalyticsTrainingInstitute
9591793303
Koramangala 1st block, Jakasandra,Near HDFC
Bank,Bangalore-560034
2. SAS Programming Base and Advanced
SAS Base Programming:
SAS Programming 1:
Introduction SAS system and Getting Familiar to SAS environment
Creating Libraries and Datasets using Data Step
Producing List Reports using Proc Step
Data Manipulation Techniques using
Data Step Vs Proc Step
Format Vs Informat
Reading raw data files using Infile and Proc Import statement
PDV
Examining Errors in SAS programing
Conditional processing using If, Where, Keep, Drop statement
Remove Duplicate records using Proc Sort
Combining SAS dataset using SAS Merge and Set statement
Summary Reports
Proc Means, Proc Freq, Proc Summary, Proc Univariate, Proc Report, Proc Tabulate
SAS Programming 2:
Introduction to Base SAS programming with Statements, Options and Functions
Controlling Input and Output observation
Data Manipulation Techniques using
Writing Multiple Dataset
Data Transformation
Transposing and Expanding Dataset
SAS Functions (Numeric and Character)
Writing to External File
Creating An Accumulating Total Variable
Combining Duplicate Records Using First. And Last.
Reading Delimited Raw Data File in .txt (text File),.csv (CSV File),.xlsx (Excel File) and .accdb (Access Database)
DSD, DLM, MISSOVER,TRUNCOVER,STOPOVER and FLOWOVER options used in reading raw data file
Connecting SAS to Other Database Server
Debugging Techniques
Put Statement
Debug Options
Processing Data Interactively
DO Loop
SAS Arrays
SAS Advanced Programming:
SAS SQL Processing
Accessing Data Using SQL
Generate detail reports by working with a single table or joining tables using PROC SQL and the appropriate options
Generate summary reports by working with a single table or joining tables using PROC SQL and the appropriate options
Construct sub queries within a PROC SQL step
Compare solving a problem using the SQL procedure versus using traditional SAS programming techniques
Access Dictionary Tables using the SQL procedure
Demonstrate advanced PROC SQL skills by creating and updating tables, updating data values, working with indexes using the
macro interface/creating macro variables with SQL, defining integrity constraints, SQL views and SET operators
Macro Processing
Creating and using user-defined and automatic macro variables within the SAS Macro Language
Automate programs by defining and calling macros using the SAS Macro Language
3. Understand the use of macro functions
Recognize various system options that are available for macro debugging and displaying values of user-defined and automatic
macro variables in the SAS log
Advanced Programming Techniques
Demonstrate advanced data set processing techniques such as updating master data sets, transposing data, combining/merging
data, sampling data, using generation data sets, integrity constraints and audit trails
Reduce the space required to store SAS data sets and numeric variables within SAS data sets by using compression techniques,
length statements or DATA step views
Develop efficient programs by using advanced programming techniques such as permanent formats and array processing
Use SAS System options and SAS data set options for controlling memory usage
Control the processing of variables and observations in the DATA step
Create sorted or indexed data in order to avoid unnecessary sorts, eliminate duplicate data and to provide more efficient data
access and retrieval
Use PROC DATASETS to demonstrate advanced programming skills (e.g. renaming columns, displaying metadata, creating indexes,
creating integrity constraints, creating audit trails)
SAS Project-Practical
EXCEL Base and Advanced
Excel Base:
Introduction MS Excel
Navigation technique in Excel
Cells Reference, Range, Rows and Columns
Format Paint, Border Style and Designing, Cell Merging, Conditional Formatting, Sorting and filtering, Data Validation,
Data consolidation
Data Import and Export
Basic Pivot Table, Chart
Excel Formulas and Functions like IF and Nested IF, Vlook-up, HLook-up, Sum,Sum IF,Match, Offset and Index etc.
Running Manual Excel Macro and Recording
Excel Advanced:
Advanced Data Manipulation Techniques
Advanced Pivot Design
Advanced Pivot Options for reporting
Power Pivot technique
Excel Dashboard using Excel functions and VBA Macros
Excel VBA Programming
Excel Project-Practical
ACCESS Base and Advanced
ACCESS Base and Advanced:
Introduction MS ACCESS
Navigation technique in ACCESS and Access Objects
Creating Database, Tables, Field Properties
Access Queries (Select, Make Table, Append, Update, Delete, Crosstab, Union and Union All)
Data Import and Export in Access
Access Pivot Table, Chart
Access Join
Forms and Reports
Access Formulas and Functions
4. Access Modules using Access VBA
Access Data Manipulation technique using SQL queries
Access Project-Practical
Qlikview and Tableau BI Dashboard Making
Introduction to Qlikview
Various data & dash board related options
Creating dashboards using Qlikview
Introduction to tableau
Various data & dash board related options
Creating dashboards using Tableau
Basic and Advanced Data analytics
Introduction to basic descriptive statistics
Introduction to basic statistical analysis
o Hands-on exercises
Data exploration & Data preparation
o Hands-on exercises
Linear Regression model building
o Hands-on exercises on simple linear model
o Hands-on exercises on multiple linear models
Logistic Regression model building
o Hands-on exercises on Logistic Regression
Customer segmentation using cluster analysis
o Hands-on exercises on sample data
Decision tree models
o Hands on exercises on sample data
Hypothesis testing with examples
o Hands on exercises on sample data
Time series forecasting
o Hands on excesses on prediction
Step by step process of credit risk model building
Data analysis practical project
Practical Data importing, Data cleaning
Analysis design
Creating the BI report
Designing the analysis solution
Performing the analysis and building a predictive model
Presentation of result
Final documentation