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Duration 2 Days 12 CPD hours This course is intended for Report authors working with dimensional data sources. Through interactive demonstrations & exercises, participants will learn how to author reports that navigate & manipulate dimensional data structures using the specific dimensional functions & features available in IBM Cognos Analytics. Introduction to Dimensional Concepts Identify different data sources and models Investigate the OLAP dimensional structure Identify dimensional data items and expressions Differentiate the IBM Cognos Analytics query language from SQL and MDX Differentiate relational and dimensional report authoring styles Introduction to Dimensional Data in Reports Work with members Identify sets and tuples in IBM Cognos Analytics Dimensional Report Context Understand the purpose of report context Understand how data is affected by default and root members Focus Your Dimensional Data Compare dimensional queries to relational queries Explain the importance of filtering dimensional queries Evaluate different filtering techniques Filter based on dimensions and members Filter based on measure values Filter using a slicer Calculations & Dimensional Functions Use IBM Cognos Analytics dimensional functions to create sets and tuples Perform arithmetic operations in OLAP queries Identify coercion errors and rules Functions for Navigating Dimesional Hierarchies Navigate dimensional data using family functions Relative Functions Navigate dimensional data using relative functions Navigate dimensional data using relative time functions Advanced Drilling Techniques & Member Sets Understand default drill-up and drill-down functionality Identify cases when you need to override default drilling behavior Configure advanced drilling behavior to support sophisticated use cases Define member sets to support advanced drilling Define member sets to support functions Set Up Drill-Through Reports Navigate from a specific report to a target report Drill down to greater detail and then navigate to target report Navigate between reports created using different data sources End-to-End Workshop Review concepts covered throughout the course

Duration 1 Days 6 CPD hours This course is intended for This course is intended for: Data platform engineers Architects and operators who build and manage data analytics pipelines 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 batch data 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 learn to build batch data analytics solutions using Amazon EMR, an enterprise-grade Apache Spark and Apache Hadoop managed service. You will learn how Amazon EMR integrates with open-source projects such as Apache Hive, Hue, and HBase, and with AWS services such as AWS Glue and AWS Lake Formation. The course addresses data collection, ingestion, cataloging, storage, and processing components in the context of Spark and Hadoop. You will learn to use EMR Notebooks 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 EMR. Module A: Overview of Data Analytics and the Data Pipeline Data analytics use cases Using the data pipeline for analytics Module 1: Introduction to Amazon EMR Using Amazon EMR in analytics solutions Amazon EMR cluster architecture Interactive Demo 1: Launching an Amazon EMR cluster Cost management strategies Module 2: Data Analytics Pipeline Using Amazon EMR: Ingestion and Storage Storage optimization with Amazon EMR Data ingestion techniques Module 3: High-Performance Batch Data Analytics Using Apache Spark on Amazon EMR Apache Spark on Amazon EMR use cases Why Apache Spark on Amazon EMR Spark concepts Interactive Demo 2: Connect to an EMR cluster and perform Scala commands using the Spark shell Transformation, processing, and analytics Using notebooks with Amazon EMR Practice Lab 1: Low-latency data analytics using Apache Spark on Amazon EMR Module 4: Processing and Analyzing Batch Data with Amazon EMR and Apache Hive Using Amazon EMR with Hive to process batch data Transformation, processing, and analytics Practice Lab 2: Batch data processing using Amazon EMR with Hive Introduction to Apache HBase on Amazon EMR Module 5: Serverless Data Processing Serverless data processing, transformation, and analytics Using AWS Glue with Amazon EMR workloads Practice Lab 3: Orchestrate data processing in Spark using AWS Step Functions Module 6: Security and Monitoring of Amazon EMR Clusters Securing EMR clusters Interactive Demo 3: Client-side encryption with EMRFS Monitoring and troubleshooting Amazon EMR clusters Demo: Reviewing Apache Spark cluster history Module 7: Designing Batch Data Analytics Solutions Batch data analytics use cases Activity: Designing a batch data analytics workflow Module B: Developing Modern Data Architectures on AWS Modern data architectures

Learn essential techniques for successful trading & investing through Technical Analysis Masterclass. Explore key indicators, chart patterns, and strategies to decipher market trends effectively.

Unlock the power of data with our comprehensive course on Business and Data Analysis with SQL. Learn essential SQL skills to extract meaningful insights, make data-driven decisions, and drive business success. Whether you're a beginner or looking to enhance your expertise, our course empowers you with the tools and knowledge needed to excel in the dynamic world of data analysis. Enroll now to master SQL for business intelligence and elevate your analytical skills to new heights.

Unlock the power of data with our 'Sales Analysis in Excel' course. Dive into e-commerce sales analysis and craft insightful sales analysis reports. Discover how to manipulate sales data, forecast trends, and automate workbook functionality. Elevate your career with advanced Excel skills! Learning Outcomes of Sales Analysis in Excel: Master data manipulation techniques for e-commerce sales analysis. Create comprehensive sales reports with Excel's advanced functions. Visualize data effectively using charts, PivotTables, and PivotCharts. Forecast future trends and make data-driven decisions. Automate repetitive tasks to boost efficiency and productivity. Why buy this Sales Analysis in Excel? Unlimited access to the course for forever Digital Certificate, Transcript, student ID all included in the price Absolutely no hidden fees Directly receive CPD accredited qualifications after course completion Receive one to one assistance on every weekday from professionals Immediately receive the PDF certificate after passing Receive the original copies of your certificate and transcript on the next working day Easily learn the skills and knowledge from the comfort of your home Certification After studying the course materials of the Sales Analysis in Excel there will be a written assignment test which you can take either during or at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £5.99. Original Hard Copy certificates need to be ordered at an additional cost of £9.60. Who is this course for? Business analysts seeking to enhance their data analysis skills. Sales professionals aiming to leverage Excel for deeper insights. Aspiring data scientists interested in e-commerce sales data. Students and graduates looking to gain a competitive edge. Entrepreneurs striving to optimize their sales strategies. Prerequisites This Sales Analysis in Excel does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Sales Analysis in Excel was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection. Career path Data Analyst: £25,000 - £40,000 Per Annum Business Analyst: £30,000 - £50,000 Per Annum Sales Analyst: £25,000 - £45,000 Per Annum Financial Analyst: £30,000 - £55,000 Per Annum Market Research Analyst: £25,000 - £40,000 Per Annum Excel Specialist: £22,000 - £35,000 Per Annum Course Curriculum Modifying a Worksheet Insert, Delete, and Adjust Cells, Columns, and Rows 00:10:00 Search for and Replace Data 00:09:00 Use Proofing and Research Tools 00:07:00 Managing Workbooks Manage Worksheets 00:05:00 Manage Workbook and Worksheet Views 00:07:00 Manage Workbook Properties 00:06:00 Working with Functions Work with Ranges 00:18:00 Use Specialized Functions 00:11:00 Work with Logical Functions 00:23:00 Work with Date & Time Functions 00:08:00 Work with Text Functions 00:11:00 Working with Lists Sort Data 00:10:00 Filter Data 00:10:00 Query Data with Database Functions 00:09:00 Outline and Subtotal Data 00:09:00 Analyzing Data Welcome to the Course 00:03:00 Apply Intermediate Conditional Formatting 00:07:00 Apply Advanced Conditional Formatting 00:05:00 Visualizing Data with Charts Create Charts 00:13:00 Modify and Format Charts 00:12:00 Use Advanced Chart Features 00:12:00 Using PivotTables and PivotCharts Create a PivotTable 00:13:00 Analyze PivotTable Data 00:12:00 Present Data with PivotCharts 00:07:00 Filter Data by Using Timelines and Slicers 00:11:00 Working with Multiple Worksheets and Workbooks Use Links and External References 00:12:00 Use 3-D References 00:06:00 Consolidate Data 00:05:00 Creating Sparklines and Mapping Data Create Sparklines 00:07:00 MapData 00:07:00 Forecasting Data Determine Potential Outcomes Using Data Tables 00:08:00 Determine Potential Outcomes Using Scenarios 00:09:00 Use the Goal Seek Feature 00:04:00 Forecasting Data Trends 00:05:00 Using Lookup Functions and Formula Auditing Use Lookup Functions 00:13:00 Trace Cells 00:09:00 Watch and Evaluate Formulas 00:08:00 Automating Workbook Functionality Apply Data Validation 00:13:00 Search for Invalid Data and Formulas with Errors 00:04:00 Work with Macros 00:18:00