{"id":3218,"date":"2023-09-24T16:15:35","date_gmt":"2023-09-24T10:15:35","guid":{"rendered":"https:\/\/infosystemltd.com\/?post_type=product&#038;p=3218"},"modified":"2023-09-25T15:38:24","modified_gmt":"2023-09-25T09:38:24","slug":"big-data-analytics-bi-and-cloud-computing","status":"publish","type":"product","link":"https:\/\/infosystemltd.com\/training-courses\/big-data-analytics-bi-and-cloud-computing\/","title":{"rendered":"BD Analytics, BI &#038; Cloud Computing"},"content":{"rendered":"\t\t<div data-elementor-type=\"product-post\" data-elementor-id=\"3218\" class=\"elementor elementor-3218\" data-elementor-post-type=\"product\">\n\t\t\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-957a437 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"957a437\" data-element_type=\"section\" data-settings=\"{&quot;jet_parallax_layout_list&quot;:[]}\">\n\t\t\t\t\t\t<div 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.elementor-tabs-wrapper{flex-direction:column}.elementor-widget-tabs.elementor-tabs-view-vertical .elementor-tabs-content-wrapper{flex-grow:1;border-style:solid solid solid none}.elementor-widget-tabs.elementor-tabs-view-horizontal .elementor-tab-content{border-style:none solid solid}.elementor-widget-tabs.elementor-tabs-alignment-center .elementor-tabs-wrapper,.elementor-widget-tabs.elementor-tabs-alignment-end .elementor-tabs-wrapper,.elementor-widget-tabs.elementor-tabs-alignment-stretch .elementor-tabs-wrapper{display:flex}.elementor-widget-tabs.elementor-tabs-alignment-center .elementor-tabs-wrapper{justify-content:center}.elementor-widget-tabs.elementor-tabs-alignment-end .elementor-tabs-wrapper{justify-content:flex-end}.elementor-widget-tabs.elementor-tabs-alignment-stretch.elementor-tabs-view-horizontal .elementor-tab-title{width:100%}.elementor-widget-tabs.elementor-tabs-alignment-stretch.elementor-tabs-view-vertical .elementor-tab-title{height:100%}.elementor-tabs .elementor-tab-mobile-title{display:none}}<\/style>\t\t<div class=\"elementor-tabs\">\n\t\t\t<div class=\"elementor-tabs-wrapper\" role=\"tablist\" >\n\t\t\t\t\t\t\t\t\t<div id=\"elementor-tab-title-2271\" class=\"elementor-tab-title elementor-tab-desktop-title\" aria-selected=\"true\" data-tab=\"1\" role=\"tab\" tabindex=\"0\" aria-controls=\"elementor-tab-content-2271\" aria-expanded=\"false\">Overview<\/div>\n\t\t\t\t\t\t\t\t\t<div id=\"elementor-tab-title-2272\" class=\"elementor-tab-title elementor-tab-desktop-title\" aria-selected=\"false\" data-tab=\"2\" role=\"tab\" tabindex=\"-1\" aria-controls=\"elementor-tab-content-2272\" aria-expanded=\"false\">Course Outline<\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t\t<div class=\"elementor-tabs-content-wrapper\" role=\"tablist\" aria-orientation=\"vertical\">\n\t\t\t\t\t\t\t\t\t<div class=\"elementor-tab-title elementor-tab-mobile-title\" aria-selected=\"true\" data-tab=\"1\" role=\"tab\" tabindex=\"0\" aria-controls=\"elementor-tab-content-2271\" aria-expanded=\"false\">Overview<\/div>\n\t\t\t\t\t<div id=\"elementor-tab-content-2271\" class=\"elementor-tab-content elementor-clearfix\" data-tab=\"1\" role=\"tabpanel\" aria-labelledby=\"elementor-tab-title-2271\" tabindex=\"0\" hidden=\"false\"><h2>Training Title: Big Data Analytics, BI and Cloud Computing<\/h2><ul><li><strong>Duration<\/strong>: 3 Months; 36 Sessions (2 Hours\/Session); 72 Hours in Total<br \/><br \/><\/li><li><strong>Days<\/strong>: Friday (In Person), Sunday, Wednesday (3 Sessions a Week)<\/li><\/ul><p>\u00a0<\/p><p><img fetchpriority=\"high\" decoding=\"async\" class=\"alignnone size-full wp-image-3219\" src=\"https:\/\/infosystemltd.com\/doafazoo\/2023\/09\/big-data-bi-cloud-computing-infosystem-technology-limited.jpg\" alt=\"Big Data Analytics, BI and Cloud Computing\" width=\"1280\" height=\"1280\" title=\"\" srcset=\"https:\/\/infosystemltd.com\/doafazoo\/2023\/09\/big-data-bi-cloud-computing-infosystem-technology-limited.jpg 1280w, https:\/\/infosystemltd.com\/doafazoo\/2023\/09\/big-data-bi-cloud-computing-infosystem-technology-limited-300x300.jpg 300w, https:\/\/infosystemltd.com\/doafazoo\/2023\/09\/big-data-bi-cloud-computing-infosystem-technology-limited-1024x1024.jpg 1024w, https:\/\/infosystemltd.com\/doafazoo\/2023\/09\/big-data-bi-cloud-computing-infosystem-technology-limited-150x150.jpg 150w, https:\/\/infosystemltd.com\/doafazoo\/2023\/09\/big-data-bi-cloud-computing-infosystem-technology-limited-768x768.jpg 768w, https:\/\/infosystemltd.com\/doafazoo\/2023\/09\/big-data-bi-cloud-computing-infosystem-technology-limited-600x600.jpg 600w, https:\/\/infosystemltd.com\/doafazoo\/2023\/09\/big-data-bi-cloud-computing-infosystem-technology-limited-100x100.jpg 100w\" sizes=\"(max-width: 1280px) 100vw, 1280px\" \/><\/p><\/div>\n\t\t\t\t\t\t\t\t\t<div class=\"elementor-tab-title elementor-tab-mobile-title\" aria-selected=\"false\" data-tab=\"2\" role=\"tab\" tabindex=\"-1\" aria-controls=\"elementor-tab-content-2272\" aria-expanded=\"false\">Course Outline<\/div>\n\t\t\t\t\t<div id=\"elementor-tab-content-2272\" class=\"elementor-tab-content elementor-clearfix\" data-tab=\"2\" role=\"tabpanel\" aria-labelledby=\"elementor-tab-title-2272\" tabindex=\"0\" hidden=\"hidden\"><div class=\"row\"><div class=\"col-6\"><h3>Session 1:<\/h3><ul><li>Introduction to Data Analytics, BI, and Cloud Computing<\/li><li>Introduction to Data Analytics, Business<\/li><li>Intelligence (BI), and Cloud Computing.<\/li><li>Understanding the difference between the roles of Data<\/li><li>Analyst, BI Analyst &amp; Data Scientist in decision-making.<\/li><li>Understanding the challenges lie ahead in developing real-time refreshing BI solutions for large scale data and how<br \/>cloud computing come as a rescue.<\/li><li>Overview of popular Data Analytics Tools and Technologies.<\/li><\/ul><h3>Session 2:<\/h3><h4>Statistics \u2013 I<\/h4><ul><li>Statistics: Statistics is used in almost any field; What concepts you only require doing your job successfully as a Data<br \/>Analyst and Data Scientist?<\/li><li>Types of Data, Variable, and Frequency Distribution.<\/li><li>Plots you need to know about and in which situation you need to use which one, Use cases.<\/li><\/ul><h3>Session 3:<\/h3><h4>Statistics &#8211; II<\/h4><ul><li>Frequency Distribution, Measures of Central Tendency [Mean, Median, Mode], and Location [Quartile, Decile,<br \/>Percentile].<\/li><li>Measures of Dispersion [Range, Standard Deviation, Variance, Coefficient of Variation].<\/li><li>Measures of Shape Characteristics: Skewness, Kurtosis.<\/li><\/ul><h3>Session 4:<\/h3><h4>Statistics &#8211; III<\/h4><ul><li>Standardization of Data, Z-score.<br \/>Best way to Detect Outlier and Impute Missing Value.<\/li><li>Time Series Analysis Concepts.<\/li><li>Sampling Methods and Sampling Size Determination.<\/li><li>Cross Sectional Study, Longitudinal Study, Panel and Time Series Study.<\/li><\/ul><h3>Session 5:<\/h3><h4>Statistics &#8211; IV<\/h4><ul><li>Correlation, Linear Regression, Logistic Regression, ANOVA; When to Perform which one?<\/li><li>Hypothesis Testing use cases and when to pick which one?<\/li><li>Concept of A\/B Testing<\/li><li>P-value; Probability, Prior Probability, Posterior Probability<\/li><\/ul><h3>Session 6:<\/h3><h4>Microsoft Excel &#8211; I<\/h4><ul><li>Excel Important Functions: vlookup, xlookup, Datediff, if, ifs, sumif, countif, etc.<\/li><li>Filter, Unique, Removing Duplicates, Number Formatting<\/li><li>Conditional Formatting.<\/li><\/ul><h3>Session 7:<\/h3><h4>Microsoft Excel &#8211; II<\/h4><ul><li>Statistical Data Analysis using Excel.<\/li><\/ul><h3>Session 8:<\/h3><h4>Microsoft Excel \u2013 III<\/h4><ul><li>Web Scrapping in Microsoft Excel<\/li><li>Data Cleaning, Data Consolidation &amp; Automizing Work with Power Query<\/li><\/ul><h3>Session 9:<\/h3><h4>Microsoft Excel &#8211; IV<\/h4><ul><li>Summarizing &amp; Report Building using Pivot Table<\/li><li>Building Interactive Charts<\/li><li>Attractive Looking Dashboard Building using Microsoft Excel<\/li><\/ul><h3>Session 10:<\/h3><p>End-to-End Data Analysis Project using Microsoft Excel<\/p><h3>Session 11:<\/h3><ul><li>Cloud Architecture to work with Big Data<\/li><li>Cloud-based Data Storage and Processing: Introduction to cloud Databases, Data Warehousing, and Lake houses.<\/li><li>Difference between Database, Data Warehouse, and Lakehouse.<\/li><li>Difference between OLTP and OLAP.<\/li><li>Knowing Azure Synapsis Platform, Microsoft Fabric, Snowflake.<\/li><\/ul><h3>Session 12:<\/h3><h4>Introduction to Power BI-I<\/h4><ul><li>Leveraging Cloud Computing for scalable BI &amp; Data Analytics Solutions.<\/li><li>Getting Familiar with the Power BI User Interface, Features, Settings, Strength &amp; Weakness.<\/li><\/ul><h3>Session 13:<\/h3><h4>Power BI \u2013 II<\/h4><ul><li>Data Modelling in Power BI [Import &amp; Direct Query Mode]<\/li><li>Advantages and Disadvantages between these two methods.<\/li><li>Data Cleaning &amp; New Measures in Power BI.<\/li><\/ul><h3>Session 14:<\/h3><h4>Power BI \u2013 III<\/h4><p>DAX Measures in Power BI.<\/p><p>Taking help from Copilot, an AI Feature of Microsoft to get it all done.<\/p><h3>Session 15:<\/h3><h4>Power BI \u2013 IV<\/h4><ul><li>Getting familiar with different Charts &amp; Reporting Tables<\/li><li>Formatting of the Charts and Reports<\/li><\/ul><h3>Session 16:<\/h3><h4>Power BI \u2013 V<\/h4><ul><li>AI Powered Charts &amp; Features<\/li><li>Interpretation of the Findings<\/li><\/ul><h3>Session 17:<\/h3><h4>Power BI \u2013 VI<\/h4><ul><li>Reports and Dashboard Building using Power BI<\/li><li>Understanding different features and build aesthetically looking professional standard Dashboards.<\/li><\/ul><h3>Session 18:<\/h3><h4>Power BI \u2013 VII<\/h4><ul><li>More on Reports and Dashboard Building using Power BI<\/li><li>Adding Bookmarks, Tooltips, and Navigation to Different Page of the Reports<\/li><\/ul><h3>Session 19:<\/h3><h4>Power BI \u2013 VIII<\/h4><ul><li>Power BI Service UI &amp; Features<\/li><li>Hosting Dashboard\/Report using Power BI Service, Sharing with Other and Maintaining all the Securities.<\/li><\/ul><h3>Session 20:<\/h3><h4>Power BI \u2013 IX<\/h4><ul><li>Working on Azure Synapsis<\/li><li>Discussing the optimization of Cloud Computing Cost<\/li><li>Connecting Lakehouse, Serverless SQL Pool &amp; Power BI<\/li><li>Working with Delta Format Data, Partitioning, and Hybrid Table in Power BI<\/li><\/ul><h3>Session 21:<\/h3><h4>Power BI \u2013 X<\/h4><ul><li>How to work with Big Data and Build real-time refreshing Dashboard.<\/li><li>Working with Direct Query Method<\/li><li>Building data pipelines and processing large datasets in the cloud.<\/li><li>Ensuring data accuracy, consistency, and integrity in cloud-based analytics.<\/li><\/ul><h3>Session 22:<\/h3><h4>Power BI \u2013 XI<\/h4><ul><li>Recap of Everything we have learned so far.<\/li><\/ul><h3>Session 23:<\/h3><ul><li>Building Realtime Dashboard using Power BI and Azure Synapsis Cloud Computing Platform<\/li><\/ul><h3>Session 24:<\/h3><h4>Fundamentals of DBMS &#8211; I<\/h4><ul><li>What is Relational Database Management System?<\/li><li>ACID Property<\/li><li>How is data stored in a Relational Database?<\/li><li>Concept of Normalization.<\/li><li>What is NoSQL and BASE Property?<\/li><\/ul><h3>Session 25:<\/h3><h4>Fundamentals of DBMS &#8211; II<\/h4><ul><li>Difference Between Relational and NoSQL Database.<\/li><li>Which one you should choose in which case?<\/li><li>What is Snowflake &amp; What advantage does it provide?<\/li><li>Concepts of Micro-Partitioning and Columnar Storage.<\/li><li>Creating Trial Account in Snowflake.<\/li><li>Snowflake UI Tour.<\/li><\/ul><h3>Session 26:<\/h3><h4>Fundamentals of DBMS &#8211; III<\/h4><ul><li>Installing MySQL Database &amp; MySQL Workbench<\/li><li>Setting up another IDE to work with any Database; DBeaver<\/li><\/ul><h3>Session 27:<\/h3><h4>Fundamentals of DBMS &#8211; IV<\/h4><ul><li>Concepts of Database, Schema, Table and Fields.<\/li><li>Types of SQL Commands: DDL, DML, DCL, TCL, DQL.<\/li><li>What are the Commands under each of these categories and what each of these commands do?<\/li><li>As a Data Analyst &amp; Data Scientist which Commands you only need to Master?<\/li><li>Constraints: Primary Key, Foreign Key, Not Null, Unique, Check, Default.<\/li><li>Data Types: DATE, DATETIME, VARCHAR, INT, NUMBER, FLOAT, Auto Increment.<\/li><\/ul><h3>Session 28:<\/h3><h4>MySQL &amp; Snowflake \u2013 I<\/h4><ul><li>Designing and Creating a Database, Schema, Tables<\/li><li>Masterclass on DDL, DML, TCL &amp; DQL Commands\/Statements<\/li><\/ul><h3>Session 29:<\/h3><h4>MySQL &amp; Snowflake \u2013 II<\/h4><ul><li>Creating File Format to Bulk Insert Data<\/li><li>Bulk Insert of Data in Snowflake &amp; MySQL<\/li><li>Error Handling during Bulk Insertion<\/li><\/ul><h3>Session 30:<\/h3><h4>MySQL &amp; Snowflake \u2013 III<\/h4><ul><li>Basic Queries: SELECT, FROM, WHERE, LIKE, ILIKE, IN, DISTINCT, BETWEEN, GROUP BY, ORDER BY, LIMIT, OFFSET, ALIAS.<\/li><li>Aggregate Functions: COUNT, SUM, AVG, MIN, MAX.<\/li><li>Difference between WHERE and HAVING Clause.<\/li><\/ul><h3>Session 31:<\/h3><h4>MySQL &amp; Snowflake \u2013 IV<\/h4><ul><li>SQL Join: Left, Right, Inner, Full, Cross Join<\/li><li>UNION, UNION ALL<\/li><li>SQL Code Order of Execution<\/li><li>CASE WHEN STATEMENT AND WIDE USE OF THIS DURING DATA CLEANING, ANALYSIS AND FEATURE ENGINEERING<\/li><\/ul><h3>Session 32:<\/h3><h4>MySQL &amp; Snowflake \u2013 V<\/h4><ul><li>Sub Queries in SELECT, FROM and WHERE Clause<\/li><li>Common Table Expressions (CTE)<\/li><li>Between Sub Queries and CTE, which one is more efficient and takes less time?<\/li><\/ul><h3>Session 33:<\/h3><h4>MySQL &amp; Snowflake \u2013 VI<\/h4><ul><li>Window Functions, the most widely used SQL Commands used by Data Analysts<\/li><li>Window Functions: RANK, DENSE_RANK, ROW_NUMBER, LEAD, LAG, FIRST VALUE, AGGREGATE WINDOW FUNCTION,<br \/>FRAME SPECIFICATION, WINDOW CHAINING<\/li><\/ul><h3>Session 34:<\/h3><h4>MySQL &amp; Snowflake \u2013 VII<\/h4><ul><li>Some built-in Functions: EXTRACT, DATE_PART, TO_DATE, TO_CHAR<\/li><li>CASTING, SUBSTRING, POSITION, COALESCE, NULLIF<\/li><\/ul><h3>Session 35:<\/h3><h4>MySQL &amp; Snowflake \u2013 VIII<\/h4><ul><li>VIEW, MATERIALIZED VIEW, AND THE DIFFERENCE BETWEEN THESE<\/li><li>Recap and Review of key concepts.<\/li><li>End-to-end Project Database Creation, Data Insertion, Data Cleaning &amp; Data Analytics Project<\/li><\/ul><h3><strong>Project:<\/strong><\/h3><p>Solution of the End-to-end Project Database Creation, Data Insertion, Data Cleaning &amp; Data Analytics Project.<\/p><p>By following this training plan, participants will gain a comprehensive understanding of Statistical Methodologies, Data Analytics,<br \/>Modern Business Intelligence, and Cloud Computing concepts. They will be equipped with the necessary skills to apply these<br \/>technologies in real-world scenarios, enabling them to make data-driven decisions and leverage the power of the cloud for scalable<br \/>and efficient analytics.<\/p><p>Participants completing the projects will be a valuable asset to any company that wants to leverage datadriven decision in their growth.<\/p><\/div><\/div><\/div>\n\t\t\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"<p class=\"fs-14px color-666 mb-1\"><strong class=\"color-000\">Duration: <\/strong>3 Months<\/p>\n<p class=\"fs-14px color-666 mb-1\"><strong class=\"color-000\">Day Of Classes: <\/strong>Friday (In Person), Sunday, Wednesday (3 Sessions a Week)<\/p>\n<p>\ud835\udc13\ud835\udc2b\ud835\udc1a\ud835\udc22\ud835\udc27\ud835\udc22\ud835\udc27\ud835\udc20 \ud835\udc13\ud835\udc22\ud835\udc26\ud835\udc1e: 36 Sessions (2 Hours\/Session); 72 Hours in Total<br \/>\nDays:<\/p>\n<p class=\"fs-14px color-666 mb-1\"><strong class=\"color-000\">Digital Content:\u00a0<\/strong>Yes<\/p>\n<p class=\"fs-14px color-666 mb-1\"><strong class=\"color-000\">Certificate Format:\u00a0<\/strong>Digital &amp; Printed<\/p>\n<p><span style=\"font-weight: 400;\">\ud835\udc16\ud835\udc28\ud835\udc2b\ud835\udc24\ud835\udc2c\ud835\udc21\ud835\udc28\ud835\udc29 \ud835\udc0b\ud835\udc28\ud835\udc1c\ud835\udc1a\ud835\udc2d\ud835\udc22\ud835\udc28\ud835\udc27: 1\/2 Asadgate, Mohammadpur, Dhaka-1207<\/span><\/p>\n","protected":false},"featured_media":3236,"template":"","meta":[],"product_cat":[18],"product_tag":[],"_links":{"self":[{"href":"https:\/\/infosystemltd.com\/wp-json\/wp\/v2\/product\/3218"}],"collection":[{"href":"https:\/\/infosystemltd.com\/wp-json\/wp\/v2\/product"}],"about":[{"href":"https:\/\/infosystemltd.com\/wp-json\/wp\/v2\/types\/product"}],"version-history":[{"count":0,"href":"https:\/\/infosystemltd.com\/wp-json\/wp\/v2\/product\/3218\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/infosystemltd.com\/wp-json\/wp\/v2\/media\/3236"}],"wp:attachment":[{"href":"https:\/\/infosystemltd.com\/wp-json\/wp\/v2\/media?parent=3218"}],"wp:term":[{"taxonomy":"product_cat","embeddable":true,"href":"https:\/\/infosystemltd.com\/wp-json\/wp\/v2\/product_cat?post=3218"},{"taxonomy":"product_tag","embeddable":true,"href":"https:\/\/infosystemltd.com\/wp-json\/wp\/v2\/product_tag?post=3218"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}