77 Data Warehouse courses delivered Online

In terms of data processing and analytics, Azure Synapse Analytics is a game-changer. This course will teach you all you need to know about Azure SQL Data Warehouse, Azure Synapse Analytics Service, PolyBase, Cloud Data Warehouse, and Microsoft SQL Data Warehouse foundations.

Duration 2 Days 12 CPD hours This course is intended for Application Consultant Business Analyst Business Process Architect Business Process Owner / Team Lead / Power User Developer Enterprise Architect Solution Architect Trainer Overview This course will prepare you to: Understand the basic concepts of SAP data warehousing Position the value-added of SAP Data Warehouse Cloud Integrate on-premise SAP Sources Model in SAP Data Warehouse Cloud Consume Data in SAP Analytics Cloud This course will prepare you to:Understand the basic concepts of SAP data warehousingPosition the value-added of SAP Data Warehouse CloudIntegrate on-premise SAP SourcesModel in SAP Data Warehouse CloudConsume Data in SAP Analytics Cloud Course Outline Getting started with data warehousing and the training environment Short introduction in SAP BW Bridge and other sources SAP Data Warehouse Cloud: -Introducing SAP Data Warehouse Cloud -Describing Spaces, integration options, operations and best practices -Introducing modeling in the Data Builder -Introducing modeling the Business Layer Describing consumption options in SAP Analytics Cloud Additional aspects in SAP Data Warehouse Cloud Outlook and roadmap Additional course details: Nexus Humans DSP01 SAP Introduction to SAP Data Warehouse Cloud training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the DSP01 SAP Introduction to SAP Data Warehouse Cloud course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Duration 3 Days 18 CPD hours This course is intended for This course is intended for: Database architects Database administrators Database developers Data analysts and scientists Overview This course is designed to teach you how to: Discuss the core concepts of data warehousing, and the intersection between data warehousing and big data solutions Launch an Amazon Redshift cluster and use the components, features, and functionality to implement a data warehouse in the cloud Use other AWS data and analytic services, such as Amazon DynamoDB, Amazon EMR, Amazon Kinesis, and Amazon S3, to contribute to the data warehousing solution Architect the data warehouse Identify performance issues, optimize queries, and tune the database for better performance Use Amazon Redshift Spectrum to analyze data directly from an Amazon S3 bucket Use Amazon QuickSight to perform data analysis and visualization tasks against the data warehouse Data Warehousing on AWS introduces you to concepts, strategies, and best practices for designing a cloud-based data warehousing solution using Amazon Redshift, the petabyte-scale data warehouse in AWS. This course demonstrates how to collect, store, and prepare data for the data warehouse by using other AWS services such as Amazon DynamoDB, Amazon EMR, Amazon Kinesis, and Amazon S3. Additionally, this course demonstrates how to use Amazon QuickSight to perform analysis on your data Module 1: Introduction to Data Warehousing Relational databases Data warehousing concepts The intersection of data warehousing and big data Overview of data management in AWS Hands-on lab 1: Introduction to Amazon Redshift Module 2: Introduction to Amazon Redshift Conceptual overview Real-world use cases Hands-on lab 2: Launching an Amazon Redshift cluster Module 3: Launching clusters Building the cluster Connecting to the cluster Controlling access Database security Load data Hands-on lab 3: Optimizing database schemas Module 4: Designing the database schema Schemas and data types Columnar compression Data distribution styles Data sorting methods Module 5: Identifying data sources Data sources overview Amazon S3 Amazon DynamoDB Amazon EMR Amazon Kinesis Data Firehose AWS Lambda Database Loader for Amazon Redshift Hands-on lab 4: Loading real-time data into an Amazon Redshift database Module 6: Loading data Preparing Data Loading data using COPY Data Warehousing on AWS AWS Classroom Training Concurrent write operations Troubleshooting load issues Hands-on lab 5: Loading data with the COPY command Module 7: Writing queries and tuning for performance Amazon Redshift SQL User-Defined Functions (UDFs) Factors that affect query performance The EXPLAIN command and query plans Workload Management (WLM) Hands-on lab 6: Configuring workload management Module 8: Amazon Redshift Spectrum Amazon Redshift Spectrum Configuring data for Amazon Redshift Spectrum Amazon Redshift Spectrum Queries Hands-on lab 7: Using Amazon Redshift Spectrum Module 9: Maintaining clusters Audit logging Performance monitoring Events and notifications Lab 8: Auditing and monitoring clusters Resizing clusters Backing up and restoring clusters Resource tagging and limits and constraints Hands-on lab 9: Backing up, restoring and resizing clusters Module 10: Analyzing and visualizing data Power of visualizations Building dashboards Amazon QuickSight editions and feature

Business Intelligence: In-House Training Business Intelligence (BI) refers to a set of technology-based techniques, applications, and practices used to aggregate, analyze, and present business data. BI practices provide historical and current views of vast amounts of data and generate predictions for business operations. The purpose of Business Intelligence is the support of better business decision making. This course provides an overview of the technology and application of BI and how it can be used to improve corporate performance. What you will Learn You will learn how to: Specify a data warehouse schema Identify the data and visualization to be used for data mining and Business Intelligence Design a Business Intelligence user interface Getting Started Introductions Agenda Expectations Foundation Concepts The challenge of decision making What is Business Intelligence? The Business Intelligence value proposition Business Intelligence taxonomy Business Intelligence management issues Sources of Business Intelligence Data warehousing Data and information Information architecture Defining the data warehouse and its relationships Facts and dimensions Modeling, meta-modeling, and schemas Alternate architectures Building the data warehouse Extracting Transforming Loading Setting up the data and relationships Dimensions and the Fact Table Implementing many-to-many relationships in data warehouse Data marts Online Analytical Processing (OLAP) What is OLAP? OLAP and OLTP OLAP functionality Multi-dimensions Thinking in more than two dimensions What are the possibilities? OLAP architecture Cubism Tools OLAP variations - MOLAP, ROLAP, HOLAP BI using SOA Applications of Business Intelligence Applying BI through OLAP Enterprise Resource Planning and CRM Business Intelligence and financial information Business Intelligence User Interfaces and Presentations Data access Push-pull data access Types of decision support systems Designing the front end Presentation formats Dashboards Types of dashboards Common dashboard features Briefing books and scorecards Querying and Reporting Reporting emphasis Retrofitting Talking back Key Performance Indicators Report Definition and Visualization Typical reporting environment Forms of visualization Unconstrained views Data mining What is in the mine? Applications for data mining Data mining architecture Cross Industry Standard Process for Data Mining (CISP-DM) Data mining techniques Validation The Business Intelligence User Experience The business analyst role Business analysis and data analysis Five-step approach Cultural impact Identifying questions Gathering information Understand the goals The strategic Business Intelligence cycle Focus of Business Intelligence Design for the user Iterate the access Iterative solution development process Review and validation questions Basic approaches Building ad-hoc queries Building on-demand self-service reports Closed loop Business Intelligence Coming attractions - future of Business Intelligence Best practices in Business Intelligence

Business Intelligence: Virtual In-House Training Business Intelligence (BI) refers to a set of technology-based techniques, applications, and practices used to aggregate, analyze, and present business data. BI practices provide historical and current views of vast amounts of data and generate predictions for business operations. The purpose of Business Intelligence is the support of better business decision making. This course provides an overview of the technology and application of BI and how it can be used to improve corporate performance. What you will Learn You will learn how to: Specify a data warehouse schema Identify the data and visualization to be used for data mining and Business Intelligence Design a Business Intelligence user interface Getting Started Introductions Agenda Expectations Foundation Concepts The challenge of decision making What is Business Intelligence? The Business Intelligence value proposition Business Intelligence taxonomy Business Intelligence management issues Sources of Business Intelligence Data warehousing Data and information Information architecture Defining the data warehouse and its relationships Facts and dimensions Modeling, meta-modeling, and schemas Alternate architectures Building the data warehouse Extracting Transforming Loading Setting up the data and relationships Dimensions and the Fact Table Implementing many-to-many relationships in data warehouse Data marts Online Analytical Processing (OLAP) What is OLAP? OLAP and OLTP OLAP functionality Multi-dimensions Thinking in more than two dimensions What are the possibilities? OLAP architecture Cubism Tools OLAP variations - MOLAP, ROLAP, HOLAP BI using SOA Applications of Business Intelligence Applying BI through OLAP Enterprise Resource Planning and CRM Business Intelligence and financial information Business Intelligence User Interfaces and Presentations Data access Push-pull data access Types of decision support systems Designing the front end Presentation formats Dashboards Types of dashboards Common dashboard features Briefing books and scorecards Querying and Reporting Reporting emphasis Retrofitting Talking back Key Performance Indicators Report Definition and Visualization Typical reporting environment Forms of visualization Unconstrained views Data mining What is in the mine? Applications for data mining Data mining architecture Cross Industry Standard Process for Data Mining (CISP-DM) Data mining techniques Validation The Business Intelligence User Experience The business analyst role Business analysis and data analysis Five-step approach Cultural impact Identifying questions Gathering information Understand the goals The strategic Business Intelligence cycle Focus of Business Intelligence Design for the user Iterate the access Iterative solution development process Review and validation questions Basic approaches Building ad-hoc queries Building on-demand self-service reports Closed loop Business Intelligence Coming attractions - future of Business Intelligence Best practices in Business Intelligence

Duration 4 Days 24 CPD hours This course is intended for The primary audience for this course is data professionals, data architects, and business intelligence professionals who want to learn about data engineering and building analytical solutions using data platform technologies that exist on Microsoft Azure. The secondary audience for this course includes data analysts and data scientists who work with analytical solutions built on Microsoft Azure. In this course, the student will learn how to implement and manage data engineering workloads on Microsoft Azure, using Azure services such as Azure Synapse Analytics, Azure Data Lake Storage Gen2, Azure Stream Analytics, Azure Databricks, and others. The course focuses on common data engineering tasks such as orchestrating data transfer and transformation pipelines, working with data files in a data lake, creating and loading relational data warehouses, capturing and aggregating streams of real-time data, and tracking data assets and lineage. Prerequisites Successful students start this course with knowledge of cloud computing and core data concepts and professional experience with data solutions. AZ-900T00 Microsoft Azure Fundamentals DP-900T00 Microsoft Azure Data Fundamentals 1 - Introduction to data engineering on Azure What is data engineering Important data engineering concepts Data engineering in Microsoft Azure 2 - Introduction to Azure Data Lake Storage Gen2 Understand Azure Data Lake Storage Gen2 Enable Azure Data Lake Storage Gen2 in Azure Storage Compare Azure Data Lake Store to Azure Blob storage Understand the stages for processing big data Use Azure Data Lake Storage Gen2 in data analytics workloads 3 - Introduction to Azure Synapse Analytics What is Azure Synapse Analytics How Azure Synapse Analytics works When to use Azure Synapse Analytics 4 - Use Azure Synapse serverless SQL pool to query files in a data lake Understand Azure Synapse serverless SQL pool capabilities and use cases Query files using a serverless SQL pool Create external database objects 5 - Use Azure Synapse serverless SQL pools to transform data in a data lake Transform data files with the CREATE EXTERNAL TABLE AS SELECT statement Encapsulate data transformations in a stored procedure Include a data transformation stored procedure in a pipeline 6 - Create a lake database in Azure Synapse Analytics Understand lake database concepts Explore database templates Create a lake database Use a lake database 7 - Analyze data with Apache Spark in Azure Synapse Analytics Get to know Apache Spark Use Spark in Azure Synapse Analytics Analyze data with Spark Visualize data with Spark 8 - Transform data with Spark in Azure Synapse Analytics Modify and save dataframes Partition data files Transform data with SQL 9 - Use Delta Lake in Azure Synapse Analytics Understand Delta Lake Create Delta Lake tables Create catalog tables Use Delta Lake with streaming data Use Delta Lake in a SQL pool 10 - Analyze data in a relational data warehouse Design a data warehouse schema Create data warehouse tables Load data warehouse tables Query a data warehouse 11 - Load data into a relational data warehouse Load staging tables Load dimension tables Load time dimension tables Load slowly changing dimensions Load fact tables Perform post load optimization 12 - Build a data pipeline in Azure Synapse Analytics Understand pipelines in Azure Synapse Analytics Create a pipeline in Azure Synapse Studio Define data flows Run a pipeline 13 - Use Spark Notebooks in an Azure Synapse Pipeline Understand Synapse Notebooks and Pipelines Use a Synapse notebook activity in a pipeline Use parameters in a notebook 14 - Plan hybrid transactional and analytical processing using Azure Synapse Analytics Understand hybrid transactional and analytical processing patterns Describe Azure Synapse Link 15 - Implement Azure Synapse Link with Azure Cosmos DB Enable Cosmos DB account to use Azure Synapse Link Create an analytical store enabled container Create a linked service for Cosmos DB Query Cosmos DB data with Spark Query Cosmos DB with Synapse SQL 16 - Implement Azure Synapse Link for SQL What is Azure Synapse Link for SQL? Configure Azure Synapse Link for Azure SQL Database Configure Azure Synapse Link for SQL Server 2022 17 - Get started with Azure Stream Analytics Understand data streams Understand event processing Understand window functions 18 - Ingest streaming data using Azure Stream Analytics and Azure Synapse Analytics Stream ingestion scenarios Configure inputs and outputs Define a query to select, filter, and aggregate data Run a job to ingest data 19 - Visualize real-time data with Azure Stream Analytics and Power BI Use a Power BI output in Azure Stream Analytics Create a query for real-time visualization Create real-time data visualizations in Power BI 20 - Introduction to Microsoft Purview What is Microsoft Purview? How Microsoft Purview works When to use Microsoft Purview 21 - Integrate Microsoft Purview and Azure Synapse Analytics Catalog Azure Synapse Analytics data assets in Microsoft Purview Connect Microsoft Purview to an Azure Synapse Analytics workspace Search a Purview catalog in Synapse Studio Track data lineage in pipelines 22 - Explore Azure Databricks Get started with Azure Databricks Identify Azure Databricks workloads Understand key concepts 23 - Use Apache Spark in Azure Databricks Get to know Spark Create a Spark cluster Use Spark in notebooks Use Spark to work with data files Visualize data 24 - Run Azure Databricks Notebooks with Azure Data Factory Understand Azure Databricks notebooks and pipelines Create a linked service for Azure Databricks Use a Notebook activity in a pipeline Use parameters in a notebook Additional course details: Nexus Humans DP-203T00 Data Engineering on Microsoft Azure training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the DP-203T00 Data Engineering on Microsoft Azure course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Duration 5 Days 30 CPD hours This course is intended for The primary audience for this course is database professionals who need to fulfil a Business Intelligence Developer role. They will need to focus on hands-on work creating BI solutions including Data Warehouse implementation, ETL, and data cleansing. Overview Create sophisticated SSIS packages for extracting, transforming, and loading data Use containers to efficiently control repetitive tasks and transactions Configure packages to dynamically adapt to environment changes Use Data Quality Services to cleanse data Successfully troubleshoot packages Create and Manage the SSIS Catalog Deploy, configure, and schedule packages Secure the SSIS Catalog SQL Server Integration Services is the Community Courseware version of 20767CC Implementing a SQL Data Warehouse. This five-day instructor-led course is intended for IT professionals who need to learn how to use SSIS to build, deploy, maintain, and secure Integration Services projects and packages, and to use SSIS to extract, transform, and load data to and from SQL Server. This course is similar to the retired Course 20767-C: Implementing a SQL Data Warehouse but focuses more on building packages, rather than the entire data warehouse design and implementation. Prerequisites Working knowledge of T-SQL and SQL Server Agent jobs is helpful, but not required. Basic knowledge of the Microsoft Windows operating system and its core functionality. Working knowledge of relational databases. Some experience with database design. 1 - SSIS Overview Import/Export Wizard Exporting Data with the Wizard Common Import Concerns Quality Checking Imported/Exported Data 2 - Working with Solutions and Projects Working with SQL Server Data Tools Understanding Solutions and Projects Working with the Visual Studio Interface 3 - Basic Control Flow Working with Tasks Understanding Precedence Constraints Annotating Packages Grouping Tasks Package and Task Properties Connection Managers Favorite Tasks 4 - Common Tasks Analysis Services Processing Data Profiling Task Execute Package Task Execute Process Task Expression Task File System Task FTP Task Hadoop Task Script Task Introduction Send Mail Task Web Service Task XML Task 5 - Data Flow Sources and Destinations The Data Flow Task The Data Flow SSIS Toolbox Working with Data Sources SSIS Data Sources Working with Data Destinations SSIS Data Destinations 6 - Data Flow Transformations Transformations Configuring Transformations 7 - Making Packages Dynamic Features for Making Packages Dynamic Package Parameters Project Parameters Variables SQL Parameters Expressions in Tasks Expressions in Connection Managers After Deployment How It All Fits Together 8 - Containers Sequence Containers For Loop Containers Foreach Loop Containers 9 - Troubleshooting and Package Reliability Understanding MaximumErrorCount Breakpoints Redirecting Error Rows Logging Event Handlers Using Checkpoints Transactions 10 - Deploying to the SSIS Catalog The SSIS Catalog Deploying Projects Working with Environments Executing Packages in SSMS Executing Packages from the Command Line Deployment Model Differences 11 - Installing and Administering SSIS Installing SSIS Upgrading SSIS Managing the SSIS Catalog Viewing Built-in SSIS Reports Managing SSIS Logging and Operation Histories Automating Package Execution 12 - Securing the SSIS Catalog Principals Securables Grantable Permissions Granting Permissions Configuring Proxy Accounts Additional course details: Nexus Humans 55321 SQL Server Integration Services training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the 55321 SQL Server Integration Services course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.

Quality Guarantee: Promising training excellence, satisfaction gurantee Accredited by: CPD UK & Quality License Scheme Tutor Support: Unlimited support via email, till you complete the course Recognised Certification: Accepted by thousands of professional bodies Start Anytime: With 1 year access to the course materials Online Learning: Learn from anywhere, whenever you want This Data Mining Course - Business Intelligence will help you get knowledge about the fundamentals of data mining, data warehouse architecture and components of the data warehouse. This course at a glance Accredited by CPD UK Endorsed by Quality Licence Scheme Learn how to store and keep the data Understand the fundamentals of data mining Know what is the meaning of business intelligence Understand different types of charts Learn problem structure and decision support system Get acquainted with the characteristics of a good dashboard and link with the balance scorecard system Recognise the process of KPI development for using in the business intelligence dashboard Learn data warehouse architecture Know the components of the data warehouse Learn the basics of data mining Understand data mining applications Why Data Mining Course - Business Intelligence right for you? This Data Mining Course - Business Intelligence is designed by industry experts to provide the learners with a thorough understanding of the tools and techniques used in data mining business intelligence. This self-paced online course will also aid you with the process of storing and keeping the data safe. In addition to this, you will also get an introduction to the basics of data mining, data mining technique, data mining applications and much more. By the end of the course, you gain an understanding of the key aspects of data mining and business intelligence altogether. This career advancement online course will also help you to kickstart your career as a professional data analyst or business manager. Data Mining Course - Business Intelligence Details Accredited by CPD certificates are accepted by thousands of professional bodies and government regulators here in the UK and around the world. Many organisations look for employees with CPD requirements, which means, that by doing this course, you would be a potential candidate in your respective field.   The Quality Licence Scheme is a brand of the Skills and Education Group, a leading national awarding organisation for providing high-quality vocational qualifications across a wide range of industries. Course Curriculum Data Warehouse - How to We Store and Keep the Data What is the Meaning of Business Intelligence Starting Case in Understanding Bi Needs in Different Phase of Business Decision Making Process and Need of It Systems Problem Structure and Decision Support System Introduction to Business Intelligence Applications Dashboard & Presentation Systems Different Types of Charts and Their Usage in Bi Dashboards Characteristics of Good Dashboard and Link With Balance Score Card System Examples of Bad Design of Dashboards - You Should Avoid - Part 1 Examples of Bad Design of Dashboards - You Must Avoid Process of Kpi Development for Using in Business Intelligence Dashboard Fundamentals of Data Mining and Process Overview of Data Warehouse More Detailed Explanation of Data Warehouse and Steps in Processing Data Warehouse Architecture - Tiers Components of Data Warehouse Approach to Develop Data Structure and Models of Database Business Intelligence and Dashboard Basics of Data Mining - Meaning Basics of Data Mining - Stages of Dm Data Mining Technique - Classification Data Mining - Clustering Data Mining - Association Rules Data Mining Applications - Banking Data Mining Applications - CRM Data Mining Applications - Other Industries Who should take this course? This comprehensive Data Mining - Business Intelligence course is suitable for anyone looking to improve their job prospects or aspiring to accelerate their career in this sector and want to gain in-depth knowledge of business intelligence and data mining methods. Entry Requirements There are no academic entry requirements for this Data Mining - Business Intelligence course, and it is open to students of all academic backgrounds. However, you are required to have a laptop/desktop/tablet or smartphone and a good internet connection. Assessment Method This Data Mining - Business Intelligence course assesses learners through multiple-choice questions (MCQs). Upon successful completion of the modules, learners must answer MCQs to complete the assessment procedure. Through the MCQs, it is measured how much a learner can grasp from each section. In the assessment pass mark is 60%. Certification Endorsed Certificate from Quality Licence Scheme After successfully passing the MCQ exam you will be eligible to order the Endorsed Certificate by Quality Licence Scheme. The Quality Licence Scheme is a brand of the Skills and Education Group, a leading national awarding organisation for providing high-quality vocational qualifications across a wide range of industries. It will give you a competitive advantage in your career, making you stand out from all other applicants and employees. There is a Quality Licence Scheme endorsement fee to obtain an endorsed certificate which is £65. Certificate of Achievement from Lead Academy After successfully passing the MCQ exam you will be eligible to order your certificate of achievement as proof of your new skill. The certificate of achievement is an official credential that confirms that you successfully finished a course with Lead Academy. Certificate can be obtained in PDF version at a cost of £12, and there is an additional fee to obtain a printed copy certificate which is £35. FAQs Is CPD a recognised qualification in the UK? CPD is globally recognised by employers, professional organisations and academic intuitions, thus a certificate from CPD Certification Service creates value towards your professional goal and achievement. CPD-certified certificates are accepted by thousands of professional bodies and government regulators here in the UK and around the world. Are QLS courses recognised? Although QLS courses are not subject to Ofqual regulation, they must adhere to an extremely high level that is set and regulated independently across the globe. A course that has been approved by the Quality Licence Scheme simply indicates that it has been examined and evaluated in terms of quality and fulfils the predetermined quality standards. When will I receive my certificate? For CPD accredited PDF certificate it will take 24 hours, however for the hardcopy CPD certificate takes 5-7 business days and for the Quality License Scheme certificate it will take 7-9 business days. Can I pay by invoice? Yes, you can pay via Invoice or Purchase Order, please contact us at info@lead-academy.org for invoice payment. Can I pay via instalment? Yes, you can pay via instalments at checkout. How to take online classes from home? Our platform provides easy and comfortable access for all learners; all you need is a stable internet connection and a device such as a laptop, desktop PC, tablet, or mobile phone. The learning site is accessible 24/7, allowing you to take the course at your own pace while relaxing in the privacy of your home or workplace. Does age matter in online learning? No, there is no age limit for online learning. Online learning is accessible to people of all ages and requires no age-specific criteria to pursue a course of interest. As opposed to degrees pursued at university, online courses are designed to break the barriers of age limitation that aim to limit the learner's ability to learn new things, diversify their skills, and expand their horizons. When I will get the login details for my course? After successfully purchasing the course, you will receive an email within 24 hours with the login details of your course. Kindly check your inbox, junk or spam folder, or you can contact our client success team via info@lead-academy.org

11 in 1 "Business Intelligence" Bundle only at £53 Boost Your Career with Apex Learning and Get Noticed By Recruiters in this Hiring Season! Get Hard Copy + PDF Certificates + Transcript + Student ID Card worth £160 as a Gift - Enrol Now Give a compliment to your career and take it to the next level. This Business Intelligence bundle will provide you with the essential knowledge to shine in your professional career. Whether you want to develop skills for your next job or elevate your skills for your next promotion, this Business Intelligence bundle will help you stay ahead of the pack. Throughout the Business Intelligence programme, it stresses how to improve your competency as a person in your chosen field while also outlining essential career insights in the relevant job sector. Along with this Business Intelligence course, you will get 10 premium courses, an originalhardcopy, 11 PDF certificates (Main Course + Additional Courses) Student ID card as gifts. This Business Intelligence Bundle Consists of the following Premium courses: Course 01: Business Intelligence and Data Mining Masterclass Course 02: Financial Analysis Course 03: Introduction to Data Analysis Course 04: SAP Controlling (CO) - Product Costing S4HANA Course 05: Basic Business Finance Course 06: Statistics Essentials Course 07: Strategic Business Management Course 08: Data Protection and Data Security Level 2 Course 09: Document Control Course 10: GDPR Course 11: Applied Economics Enrol now in Business Intelligence to advance your career, and use the premium study materials from Apex Learning. How will I get my Certificate? After successfully completing the course you will be able to order your CPD Accredited Certificates (PDF + Hard Copy) as proof of your achievement. PDF Certificate: Free (Previously it was £6*11 = £66) Hard Copy Certificate: Free (For The Title Course: Previously it was £10) The bundle incorporates basic to advanced level skills to shed some light on your way and boost your career. Hence, you can strengthen your Business Intelligence expertise and essential knowledge, which will assist you in reaching your goal. Moreover, you can learn from any place in your own time without travelling for classes. Curriculum of Bundle Course 01: Business Intelligence and Data Mining Masterclass Module 01: What is Business Intelligence? Module 02: Starting Case in understanding BI needs in diff phase of business Module 03: Decision Making Process and Need of IT systems Module 04: Problem Structure and Decision Support System Module 05: Introduction to BI Applications Module 06: Dashboard presentation systems Module 07: Different Types of Charts used in 131 Dashboards Module 08: Good Dashboard and BSC Module 09: Examples of Bad Dashboards 1 Module 10: Examples of Bad Dashboards 2 Module 11: Process of KPI Development Module 12: Overview of Data warehouse Module 13: More explaining of data warehouse and steps in processing Module 14: Data Warehouse Architecture -Tiers Module 15: Data Warehouse - components Module 16: Approach to develop data structure and Models of database Module 17: Basics of Data Mining - Meaning Module 18: Basics of Data Mining - Stages of DM Module 19: Data Mining Technique - Classification Module 20: Data mining - Clustering Module 21: Data Mining - Association Rules Module 22: Data Mining Applications - Banking Module 23: Data Mining Applications - CRM Module 24: Data Mining Applications - other industries CPD 110 CPD hours / points Accredited by CPD Quality Standards Who is this course for? Anyone from any background can enrol in this Business Intelligence bundle. Requirements This course has been designed to be fully compatible with tablets and smartphones. Career path Having this expertise will increase the value of your CV and open you up to multiple job sectors. Certificates Certificate of completion Digital certificate - Included Certificate of completion Hard copy certificate - Included You will get the Hard Copy certificate for the title course Business Intelligence and Data Mining Masterclass absolutely Free! Other Hard Copy certificates are available for £10 each. Please Note: The delivery charge inside the UK is £3.99, and the international students must pay a £9.99 shipping cost.

Duration 1 Days 6 CPD hours This course is intended for This course is intended for data warehouse engineers, data platform engineers, and architects and operators who build and manage data analytics pipelines. Completed either AWS Technical Essentials or Architecting on AWS Completed Building Data Lakes on AWS Overview In this course, you will learn to: Compare the features and benefits of data warehouses, data lakes, and modern data architectures Design and implement a data warehouse analytics solution Identify and apply appropriate techniques, including compression, to optimize data storage Select and deploy appropriate options to ingest, transform, and store data Choose the appropriate instance and node types, clusters, auto scaling, and network topology for a particular business use case Understand how data storage and processing affect the analysis and visualization mechanisms needed to gain actionable business insights Secure data at rest and in transit Monitor analytics workloads to identify and remediate problems Apply cost management best practices In this course, you will build a data analytics solution using Amazon Redshift, a cloud data warehouse service. The course focuses on the data collection, ingestion, cataloging, storage, and processing components of the analytics pipeline. You will learn to integrate Amazon Redshift with a data lake to support both analytics and machine learning workloads. You will also learn to apply security, performance, and cost management best practices to the operation of Amazon Redshift. Module A: Overview of Data Analytics and the Data Pipeline Data analytics use cases Using the data pipeline for analytics Module 1: Using Amazon Redshift in the Data Analytics Pipeline Why Amazon Redshift for data warehousing? Overview of Amazon Redshift Module 2: Introduction to Amazon Redshift Amazon Redshift architecture Interactive Demo 1: Touring the Amazon Redshift console Amazon Redshift features Practice Lab 1: Load and query data in an Amazon Redshift cluster Module 3: Ingestion and Storage Ingestion Interactive Demo 2: Connecting your Amazon Redshift cluster using a Jupyter notebook with Data API Data distribution and storage Interactive Demo 3: Analyzing semi-structured data using the SUPER data type Querying data in Amazon Redshift Practice Lab 2: Data analytics using Amazon Redshift Spectrum Module 4: Processing and Optimizing Data Data transformation Advanced querying Practice Lab 3: Data transformation and querying in Amazon Redshift Resource management Interactive Demo 4: Applying mixed workload management on Amazon Redshift Automation and optimization Interactive demo 5: Amazon Redshift cluster resizing from the dc2.large to ra3.xlplus cluster Module 5: Security and Monitoring of Amazon Redshift Clusters Securing the Amazon Redshift cluster Monitoring and troubleshooting Amazon Redshift clusters Module 6: Designing Data Warehouse Analytics Solutions Data warehouse use case review Activity: Designing a data warehouse analytics workflow Module B: Developing Modern Data Architectures on AWS Modern data architectures