Data Analyst-Python/ETL/SSIS/SSRS/SSAS/Microsoft SQL/PowerBI

Data Analyst-Python/ETL/SSIS/SSRS/SSAS/Microsoft SQL/PowerBI, available at $54.99, has an average rating of 1, with 125 lectures, based on 1 reviews, and has 46 subscribers.

You will learn about Analyse Data with Python Visualise Data with Python Clean Data with Python Create an ETL Process Create SSIS Package to Extract, Transform and Load Data Create reports with SSRS Create a Tabular Model with SSAS Create Key Performance Indicators – KPI's Create calculated columns Creating measures Analyse data with SSAS Analyse data with Microsoft SQL (T-SQL) Connect to multiple data sources with Power BI Analyse data with Power BI Visualise data with Power BI Analyse and visualise data on SQL Server Database with Power BI This course is ideal for individuals who are Beginner Data Analyst or Beginner Data Scientist or Beginner Business Intelligence Analyst It is particularly useful for Beginner Data Analyst or Beginner Data Scientist or Beginner Business Intelligence Analyst.

Enroll now: Data Analyst-Python/ETL/SSIS/SSRS/SSAS/Microsoft SQL/PowerBI

Summary

Title: Data Analyst-Python/ETL/SSIS/SSRS/SSAS/Microsoft SQL/PowerBI

Price: $54.99

Average Rating: 1

Number of Lectures: 125

Number of Published Lectures: 125

Number of Curriculum Items: 125

Number of Published Curriculum Objects: 125

Original Price: $74.99

Quality Status: approved

Status: Live

What You Will Learn

Analyse Data with Python
Visualise Data with Python
Clean Data with Python
Create an ETL Process
Create SSIS Package to Extract, Transform and Load Data
Create reports with SSRS
Create a Tabular Model with SSAS
Create Key Performance Indicators – KPI's
Create calculated columns
Creating measures
Analyse data with SSAS
Analyse data with Microsoft SQL (T-SQL)
Connect to multiple data sources with Power BI
Analyse data with Power BI
Visualise data with Power BI
Analyse and visualise data on SQL Server Database with Power BI

Who Should Attend

Beginner Data Analyst
Beginner Data Scientist
Beginner Business Intelligence Analyst

Target Audiences

Beginner Data Analyst
Beginner Data Scientist
Beginner Business Intelligence Analyst

Data is everywhere. Everything you do online and in your daily life generates data—and it’s a valuable business resource. In fact, 94% of companies say data and analytics are essential to their growth. As we move toward greater digitization, there is an ever-increasing demand for professionals who can turn information into actionable insights.

A data analyst is a person whose job is to gather and interpret data in order to solve a specific problem. The role includes plenty of time spent with data but entails communicating findings too.

Here’s what many data analysts do on a day-to-day basis:

Gather data: Analysts often collect data themselves. This could include conducting surveys, tracking visitor characteristics on a company website, or buying datasets from data collection specialists.

Clean data: Raw data might contain duplicates, errors, or outliers. Cleaning the data means maintaining the quality of data in a spreadsheet or through a programming language so that your interpretations won’t be wrong or skewed.

Model data: This entails creating and designing the structures of a database. You might choose what types of data to store and collect, establish how data categories are related to each other, and work through how the data actually appears.

Interpret data: Interpreting data will involve finding patterns or trends in data that could answer the question at hand.

Present: Communicating the results of your findings will be a key part of your job. You do this by putting together visualizations like charts and graphs, writing reports, and presenting information to interested parties

During the process of data analysis, analysts often use a wide variety of tools to make their work more accurate and efficient. Some of the most common tools in the data analytics industry include:

Microsoft Excel
Google Sheets

Tableau

R or Python

SSAS

SSRS

SSIS

Microsoft Power BI

Jupyter Notebooks

Course Curriculum

Chapter 1: Python & Jupyter Notebook Setup

Lecture 1: Introduction

Lecture 2: What is a Data Analyst

Lecture 3: What is Python

Lecture 4: What is Jupyter Notebook

Lecture 5: Installing Jupyter Notebook Server

Lecture 6: Running Jupyter Notebook Server

Lecture 7: Common Jupyter Notebook Commands

Lecture 8: Jupyter Notebook Components

Lecture 9: Jupyter Notebook Dashboard

Lecture 10: Jupyter Notebook User Interface

Lecture 11: Creating a new Notebook

Chapter 2: Data Analysis & Visualization with Python

Lecture 1: Kaggle Datasets

Lecture 2: Tabular Data

Lecture 3: Exploring Pandas Data Frame

Lecture 4: Manipulating a Pandas Data Frame

Lecture 5: What is Data Cleaning

Lecture 6: Performing Data Cleaning

Lecture 7: What is data visualization

Lecture 8: Visualizing qualitative data

Lecture 9: Visualizing quantitative data

Chapter 3: SQL Server Setup

Lecture 1: What is SQL Server

Lecture 2: SQL Server Installation Requirements

Lecture 3: SQL Server Editions

Lecture 4: Download SQL Server

Lecture 5: Install SQL Server

Lecture 6: Install SQL Server Management Studio (SSMS )

Lecture 7: Connect SSMS to SQL Server

Lecture 8: Please Note

Lecture 9: Restore sample data warehouse database

Lecture 10: Restore sample database

Chapter 4: Visual Studio Setup

Lecture 1: What is Visual Studio

Lecture 2: Visual studio installation requirements

Lecture 3: Install Visual studio

Lecture 4: Visual studio workloads

Lecture 5: Install SQL Server Data Tools (SSDT)

Lecture 6: Install SSDT Templates

Lecture 7: Overview of Data Analyst-Python/ETL/SSIS/SSRS/SSAS/Microsoft SQL/PowerBI

Chapter 5: Data Analysis with ETL & SSIS

Lecture 1: What is ETL

Lecture 2: What is SSIS

Lecture 3: ETL Illustration

Lecture 4: Create a new SSIS Project

Lecture 5: SSIS Designer

Lecture 6: Add and configure a Flat File Connection Manager

Lecture 7: Remapping Column Data Types

Lecture 8: Add and configure OLE DB connection manager

Lecture 9: Add a Data Flow task to the package

Lecture 10: Add and configure the flat file source

Lecture 11: Add and configure the lookup transformations

Lecture 12: Add and configure Lookup for DateKey Transformation

Lecture 13: Add and configure OLEDB Destination

Lecture 14: Run and test Package

Chapter 6: Create Analytic Reports with SSRS

Lecture 1: What is SSRS

Lecture 2: Create a report server project

Lecture 3: Create a report definition file

Lecture 4: Configure a data source for the report

Lecture 5: Define a dataset for the report

Lecture 6: Add a table to the report

Lecture 7: Format report

Lecture 8: Group data in report

Lecture 9: Adding totals to the report

Lecture 10: Previewing report

Lecture 11: Exporting report

Chapter 7: Data Analysis with SQL Server Analysis Server (SSAS)

Lecture 1: What is SSAS

Lecture 2: Installing SSAS

Lecture 3: Connecting SSAS

Lecture 4: Create a tabular model

Lecture 5: Explore tabular model authoring

Lecture 6: Creating connection to data source

Lecture 7: Transform and import data

Lecture 8: Mark as a data table

Lecture 9: Create table relationships

Lecture 10: Create calculated columns- part 1

Lecture 11: Create calculated columns- part 2

Lecture 12: Creating measures – Part 1

Lecture 13: Creating measures – Part 2

Lecture 14: Creating measures – Part 3

Lecture 15: Creating KPI's

Chapter 8: Data Analysis with Microsoft SQL(T-SQL)

Lecture 1: What is SQL

Lecture 2: What is Microsoft SQL (T-SQL )

Lecture 3: Analysing data with Analytic Functions

Lecture 4: Basic Analytic Function Syntax

Lecture 5: Analysing data with LEAD Function

Lecture 6: Analysing data with LAG Function

Lecture 7: Analysing data with LAST_VALUE Function

Lecture 8: Analysing data with FIRST_VALUE Function

Lecture 9: Analysing data with PERCENT_RANK Function

Lecture 10: Analysing data with CAST Function

Lecture 11: Analysing data with CONVERT Function

Lecture 12: Analysing data with SUBSTRING Function

Lecture 13: Analysing data with CASE Expression

Chapter 9: Power BI Setup

Lecture 1: What is Microsoft 365

Instructors

Tech Academy
Real Skills For The Real World

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5 stars: 0 votes

Frequently Asked Questions

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You can view and review the lecture materials indefinitely, like an on-demand channel.

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