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Business Intelligence (BI) is a collection of techniques and tools for turning raw data into meaningful and useful information for business analysis purposes. BI technology can process large amounts of unstructured data to identify, develop and create new strategic business opportunities. Business Intelligence software is a type of application software for retrieving, analyzing, changing, and reporting business intelligence data. Applications generally read data that has been stored before, although it does not have to be in the data or data warehouse. This MSBI Training by Eduranz allows you to master MSBI tools such as SSIS, SSRS, and SSAS with SQL Server. This MSBI training also helps you remove MCSE: Certificate of Business Analysis. As part of this training, you will learn how to integrate data and produce reports, dashboards and cubes to help make reports faster. As part of your online training, you will receive additional Microsoft courses in Data Analysis with SQL Server Reporting Services.
|Section 1:Introduction to Social Media|
|Introduction to Social Media||FREE||00:30:00|
|Building Social Authority||00:20:00|
|Mobile Social Media||00:30:00|
|Section 2: Types & Conclusion|
|Classification of Social Media||00:25:00|
|Advertising on Social Media||00:35:00|
|Social Media in Classroom||00:30:00|
|General Knowledge Quiz||00:05:00|
This MSBI certification training gives you all the knowledge you need to work with the Microsoft Business Intelligence stack. You gain experience in analyzing, integrating, and reporting on SQL Server. This course gives you enough knowledge about data warehousing, ETL solutions, connection managers, transformations and other processes. You will also receive an official Microsoft Courseware for data analysis with the SQL Server Reporting Service.
What will you learn in this MSBI online training?
Microsoft Business Intelligence Architecture
Data modeling, representation and transformation for BI
Multidimensional Modeling, ETL, and Transformation Concepts in SSIS
SSIS architecture, SSAS and SSR and its components
Example of data flow through components
Create charts, reports and dashboards with SSRS
Draft for OLAP databases and tables in SSAS
Creation and processing of new data sources and new cubes
Defines various types of relationships in SSAS
MCSE Preparation: Business Intelligence Certification Exam
Who should attend this MSBI training?
Software architect, ETL developer, and data analyst
Business Intelligence Experts and people who want to improve MSBI
What are the requirements for studying MSBI?
Anyone can start this online training and study at MSBI.
Why should you study MSBI training online?
There is an increasing demand for SQL Server Business Intelligence experts today and there is an urgent need for SSAS, SSIS and SSR expertise. Therefore, in this lesson, you can master the highly desirable Microsoft BI tasks and pass the MCSE: Certificate of Business Analysis for a great future.
Introduction to business intelligence, understanding data modeling concepts, data cleaning, training in data analysis, data presentation, data transformation.
Introduction to ETL which includes steps to extract, convert, load, use user email IDs to read flat files, extract user IDs from email IDs, load data into database tables.
Introduction to Relationship Managers – Representation of Logical Connections, Different Types of Relationship Managers – Basic Files, Databases, Faster Loads with OLE DB, Comparison of OLE DB and ADO.net Productivity, Bulk Insertion Training, Working with Excel Link Managers, and Problem Identification.
Learn about converting data, converting data from one format to another, understanding the concepts for converting map cards, converting data columns and copying columns, converting import and export columns, converting scripts and OLEDB commands, basics for scanning lines, aggregation and sorting , percentage and line scan
Understanding Pivot and UnPivot Transformations, Understanding Validation and Line Conversions, Working with Split and Join Transformations, Studying Request and Cache Conversions, Integrating with Azure Analytics Services, MSBI Elastic Alerts for Azure Cloud Service Integration, Scaling MSBI deployment options, handling cloud data sources, and query analysis. Extending the SSIS suite, provisions for tighter windows, working with more data sources, SQL Server vNext to improve SQL Server capabilities, a wider choice of development languages and data types both on-site and in the cloud.
Understanding data that slowly changes over time, learning the process of writing new data into old data, best practices. Detailed description of the three types of SCD – Type1, Type2 and Type3 and their differences.
Understanding how fuzzy search transformation differs from search transformation, the concept of fuzzy compatibility
Information about configuring lines for errors, recording packages, determining package configurations, understanding constraints, and processing events.
Learn about SSR architecture, SSR reporting program components, and data flow in various components.
Understand the concepts of Matrix and Tablix, work with text fields, formatting training, row / column grouping, basics on sorting, formatting, concept of title, footer, totals, subtotals, and page details.
Parameters training, filtering and visibility expressions, breakthrough and breakthrough understanding, variable definitions, custom code.
Introduction to various aspects of graphs, line graphs, combined graphs, graphic formats, sub-reports, integration of performance requirements and M-language with SSRS, working with additional data sources on MSBI, extensive transformation options other than MSBI, using M functions written for PBIX in SSRS created.
Learn how to create mini-dash dashboards, data bars, charts, flowcharts, and drill reports, the basics of ad hoc reporting.
Data Bars, Sparklines, Indicators, Dimensions, Map Charts, Blow Reports, What is Ad Hoc Reporting?
Understand report caching, authorization, authentication, and report snapshots, subscription training, and site security.
Understand the concept of multi-dimensional analysis, understand the architecture and benefits of SSAS, learn how the cube works, work with OLAP tables and databases, understand the concept of data sources, work with dimensional wizards, understand dimensional structures and flexible and firm connection relationships.
Training on process dimensions, process database, cube making, cube tree understanding, cube tracking, defining various categories, product and client keys, column naming, cube processing, and distribution, reporting with cu.Hands-on Exercise – Create a cube and name it a different column. Expand the cube after applying other keys and rules. Create a cube report
Understand the dimensions of data and their meaning, various regular, abstract, many-to-many relationships that work on data partitioning and aggregation.
Familiarize yourself with the SSAS cube, the different types of cubes, the size of the cube, and its comparison with the data warehouse.
Various operations on the cube, limitations of the OLAP cube, memory analysis architecture, and its benefits.
Give the cube the available storage capacity to provide self-service business intelligence by understanding how analytics work in memory.
Hands-on Exercise – Expand the cube to get information about the supermarket
The logical model of the schema used by the cube, the components of the cube, understanding nominal queries, and relationships.
An overview of the concept of dimensions, which explains attributes and hierarchies of attributes, key-value pairs, reloads metadata, logical keys, and role-based dimensions.Hands-on Exercise – Create role-based dimensions, using attribute hierarchies
Understand cube size, analyze sizes, examine relationships between size and group measurements, cube features, and use dimensions.
Work with Cube Measurement, implement analytics, understand key performance metrics, implement detailed data actions and actions, work with data partitioning, summaries, translations, and perspectives.Hands-on Exercise – Work with cube metrics, provide analytics, provide detailed actions and actions for data, create data partitions
Understand languages for multidimensional expressions, work with MDX requests for data extraction, work with clauses, write to MDX, optimize, filter states.Hands-on Exercise – Apply clauses, manage and filter the status of MDX Request Data Requests
Familiarize yourself with the MDX hierarchy, functions used in MDX functions, ancestors, and ascending and descending sort operations
Hands-on Exercise – Create an MDX hierarchy and run data in ascending and descending sequences
Data Analysis Expressions (DAX) with EVALUATION and CALCULATION functions, filtering DAX queries, making calculated actions, and performing data analysis with DAXHands-on Exercise – Use the EVALUATION and CALCULATION functions, filter DAX requests, make calculated measurements, and do DAX data analysis
Design and publish tables, design relationship metrics, hierarchies, partitions, perspectives, and calculated columns
Hands-on Exercise – Design and publish worksheets with data. Design measures relationships, hierarchies, partitions, perspectives, and calculated columns
Configure and manage SQL Server Analysis Services (SSAS), Non-Union Memory Architecture (NUMA), Monitor and optimize performance, vNext SSAS spreadsheets, Excel portability, Import Power BI Desktop models, and import Power Pivot models, two-way filter links on MSBI.
Hands-on Exercise – Configure and manage SQL Server Analysis Services (SSAS), monitor and optimize performance
Read server R data from SAS, TXT or Excel formats, convert data to XDF format; The amount of data, rxCrossTabs versus rxCube, extract quanta with rxQuantile; Data visualization (rxSummary and rxCube, R histogram and rxLinePlot) Processing data with rxDataStep Changing with transformers and transformer Word processing functions with RML packages Creating prediction models with ScaleR Performing database analysis with ScaleR SQL Server
Hands-on Exercise – Read data with R Server from SAS, TXT or Excel formats, convert data to XDF format; Summarize data, extract quanta with rxQuantile; Data visualization (rxSummary, rxCube, R histogram, and rxLinePlot) Transforming with transformers and transformer functions Creating predictive models with ScaleR Perform database analysis in SQL Server database
Analyze data with SQL Server Reporting Services
- Project 1: Analysis of the Python Name Template
Challenge: How to analyze trends and the most popular baby names
Topic: In this Python project, you are working with the United States Social Security Administration (SSA), which provides data on the frequency of baby names from 1880 to 2016. This project requires data analysis by considering various methods. You will see the most common names, identify name trends, and find the most popular names for a particular year.
- Data analysis with the Pandas Library
- Provide data frame manipulation
- Land for bars and boxes with Matplotlib
- Project 2: Python Web Scraping for Science Science
In this project, you will be introduced to the web scrawling process in Python. This includes installing Beautiful Soup, scraping libraries on the Web, editing general data and web page formats, exploring main object types, navigating strings, finding search trees, navigation options, Analyzer, Search Trees, and searching CSS. Class arguments, lists, functions, and keywords.
- Project 3: Predict customer murders at telecommunications companies
Task Issues: To maximize the profitability of your telecommunications company by reducing cooling rates
Topic: In this project, you work with telecommunications company customer records. This note contains telephone client subscription data. Each column contains a telephone number, call minutes at different times, fees paid, account life, and whether the customer has canceled some services by unsubscribing. The aim is to predict whether the customer will eventually swell or not.
- Expand the Scikit-Learn ML library
- Develop code with the Jupyter Notebook
- Create a model using the execution matrix
At the time of enrollment team Eduranz will assign one mentor for you and he will be guiding you in this lifetime Journey.
24/7 Tech Adviser Support
Lifetime 24/7 Technical and Non Technical Support from team Eduranz.
Get Lifetime opportunity to access and attend the live sessions multiple times.
Assignments & Quizzes
Every module will be followed by certification based assessment and quiz.
Become a Certified Professional.
Team Eduranz will update your Resume before forwarding it to our 60+ global Clients.
To run Python, your system must meet the following basic requirements:
1. 32- or 64-bit operating system
2. 1 GB RAM
The statement uses Anaconda and Jupiter notebooks. The E-learning video contains detailed installation instructions.
All of our highly qualified trainers are industry experts with at least 10-12 years of relevant teaching experience. Each of them underwent a rigorous selection process that included screening profiles, technical assessments, and training demonstrations before being certified for training. We also ensure that only high-level graduates live in our faculty.
Eduranz offers a 24/7 request solution and you can pick up your tickets at any time from our dedicated support team. You can use email support for all your questions. If your request is not answered via email, we can also arrange one-on-one discussions with the faculty. You will be glad to know that you can switch to Eduranz support after completing training. We also don’t limit the number of tickets you can collect when solving questions and doubts.
Eduranz offers independent learning for those who want to learn at their own pace. This training also gives you the benefits of email questions, tutorial sessions, 24×7 support, and access to modules or LMS for lifelong learning. In addition, you will receive the latest version of learning material at no additional cost. Independent Eduranz training is 75% lower than teacher-led online training. If you experience problems while studying, we can arrange virtual courses directly with the trainer at any time.
Eduranz offers the most up-to-date, relevant and valuable projects in the real world as part of the training program. In this way, you can integrate what you have learned in the real industry. Each training is delivered with various projects where you can thoroughly test your skills, learning and practical knowledge so that you are well prepared for the industry. They work on very interesting projects in the fields of high technology, e-commerce, marketing, sales, networking, banking, insurance and more. After successfully completing your project, your skills will be counted as a result of six months intensive industry experience.
Eduranz actively supports all trainees who have successfully completed the training. That’s why we are involved in more than 80 top MNCs worldwide. This way you can be in exclusive organizations such as Sony, Ericsson, TCS, Mu Sigma, Standard Chartered, Cognizant, Cisco and other similar-sized companies. We also support you during job interviews and preparation of your CV.
In any case, you can switch from self-directed self-training to online training only by paying an additional amount and participating in the next set of training that will be specifically notified to you.
After completing the Eduranz Training Program along with all real projects, tests and assignments and achieving at least 60% points in the qualification exam; You received a certificate that was certified by Eduranz. This certification is recognized by Eduranz’s partner organizations, which includes a lot of top MNCs worldwide that are also part of the Fortune 500 list.
In our job support program, we help you start your dream job by sharing your resume with potential tenants, helping you make resumes, and preparing you for interview questions. Eduranz training should not be seen as an employment agency or employment guarantee, because the entire employment process is handled directly between the student and the employing company and the final choice is always left to the employer.