355 Analytics courses in Leven delivered Live Online

Microsoft Excel® in Depth: In-House Training The goal of this course is to provide a deeper understanding of Excel and its intricacies and a new ability to use it efficiently producing the best solutions for your projects. This practical course provides a solid background of the features of Excel and a deeper understanding of its features, benefits and uses. This is not a beginner's course in Excel. You will learn some advanced features such as Pivot Tables, Charting, Tables, Sorting, Filtering and Functions. The goal of this course is to provide a deeper understanding of Excel and its intricacies and a new ability to use it efficiently producing the best solutions for your projects. What you Will Learn You'll learn how to: Use functions like IF, AVERAGE, SUMIF, SUMIFS, SUMPRODUCT, INDEX, MATCH, CHOOSE, DATE, and many more Create meaningful charts Use pivot tables Use Conditional Formatting, Data Validation Take advantage of using Named ranges, do sorting, filtering, tables Getting Started The building blocks of Excel, built-in functions, will be examined The basics of formatting your data will be examined Shortcuts and data manipulation will be explored Built-in features like those mentioned in the 'What you will learn' section above will be explored in detail Excel Functions - VLOOKUP, IF, INDEX, MATCH, CHOOSE, SUMIF, SUMIFS, SUMPRODUCT, DATE, so many more Using Named ranges, Data Validation, Sorting, and Filtering Learn the Name manager; Learn the difference between local and global names; Ensure correct access to linked workbooks; Ensure data accuracy; Learn how to use cascading data validation (for example, once a user chooses 'cars', another cell allows only Ford, Toyota, etc.); Sorting by more than 3 fields; Filtering by font, pattern, or value; See your data based on things like dates in the 3rd quarter, or fields where quantity x price is greater than some fixed value Conditional formatting and data formatting Make relevant data stand out Isolate highs and lows Make error cells invisible Learn about Data bars, Icon sets, and Color scales Highlight differences between worksheets Learn all the codes in the Format/Number list Using cell Styles Learn all about alignment, protection, borders, colors and more Pivot Tables Learn how to summarize large amounts of data with a few clicks Learn various ways of presenting the data Learn the various pivot table tools Learn how to customize and format a pivot table to suit your needs Learn how to group data Learn how to use the various options to present your data Charts Learn how to create a chart with one keystroke! Learn the 11 types of built-in charts Learn how to create a chart with one keystroke! Learn how to customize the charts to make the information tell the right story Learn how to use the design, layout, and formatting available to charts in Excel 2007 Learn embedded charts versus chart sheets Learn how to use modify all the pieces of a chart Array formulas Learn how to use the most powerful formulas in Excel Learn how to combine many formulas into one compact array-formula Learn the real power of these formulas and why regular formulas can't do the job Learn how to use built-in array formulas, like TREND or TRANSPOSE

Duration 4 Days 24 CPD hours This course is intended for Data Modelers Overview Please refer to course overview This offering provides participants with introductory to advanced knowledge of metadata modeling concepts, and how to model metadata for predictable reporting and analysis results using Framework Manager. Participants will learn the full scope of the metadata modeling process, from initial project creation, to publishing of metadata to the web, enabling end users to easily author reports and analyze data. Introduction to IBM Cognos Framework Manager Model data and identifying related data Define requirements and modeling strategies Overview of IBM Cognos Framework Manager Create a baseline project Extend a model Prepare reusable metadata Model for predictable results in IBM Cognos Framework Manager Identify query issues Identify reporting traps Model virtual star schemas Use query subjects, modify relationships, and consolidate metadata using virtual objects Create calculations, filter data, and customize metadata for runtime Implement a time dimension and specify determinants Model for presentation in IBM Cognos Framework Manager Create a presentation view Examine data source query subject types and stored procedure query subject types Specify data security and package security Specify object security and dynamic data security Create analysis objects Manage OLAP data sources Advanced capabilities in IBM Cognos Framework Manager Explore SQL generation and the use of governors Examine the use of IBM Cognos SQL and generated SQL for DMR data Other query considerations Use session parameters, prompt macros, and security macro functions Use materialized views, minimize SQL, and enable Dynamic Query Mode (DQM) DQM, CQM, caching metadata, query processing, aggregate calculation, and other ways to improve performance Extended capabilities in IBM Cognos Framework Manager (Optional) Perform basic maintenance and management on a model Remap metadata to another source and import and link additional data sources Run scripts to automate or update a model and report on a model Segment a project, link a project, and branch a model Nest packages and specify package languages and functions Explore additional modeling techniques and customize metadata for a multilingual audience Additional course details: Nexus Humans B6152 IBM Cognos Framework Manager - Design Metadata Models v11.0.x 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 B6152 IBM Cognos Framework Manager - Design Metadata Models v11.0.x 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 4 Days 24 CPD hours This course is intended for Data Modelers Overview Please refer to course overview This offering provides participants with introductory to advanced knowledge of metadata modeling concepts, and how to model metadata for predictable reporting and analysis results using IBM Cognos Framework Manager. Participants will learn the full scope of the metadata modeling process, from initial project creation, to publishing of metadata to the web, enabling end users to easily author reports and analyze data. Introduction to IBM Cognos Framework Manager Model data and identifying related data Define requirements and modeling strategies Overview of IBM Cognos Framework Manager Create a baseline project Extend a model Prepare reusable metadata Model for predictable results in IBM Cognos Framework Manager Identify query issues Identify reporting traps Model virtual star schemas Use query subjects, modify relationships, and consolidate metadata using virtual objects Create calculations, filter data, and customize metadata for runtime Implement a time dimension and specify determinants Model for presentation in IBM Cognos Framework Manager Create a presentation view Examine data source query subject types and stored procedure query subject types Specify data security and package security Specify object security and dynamic data security Create analysis objects Manage OLAP data sources Advanced capabilities in IBM Cognos Framework Manager Explore SQL generation and the use of governors Examine the use of IBM Cognos SQL and generated SQL for DMR data Other query considerations Use session parameters, prompt macros, and security macro functions Use materialized views, minimize SQL, and enable Dynamic Query Mode (DQM) DQM, CQM, caching metadata, query processing, aggregate calculation, and other ways to improve performance Extended capabilities in IBM Cognos Framework Manager Perform basic maintenance and management on a model Remap metadata to another source and import and link additional data sources Run scripts to automate or update a model and report on a model Segment a project, link a project, and branch a model Nest packages and specify package languages and functions Explore additional modeling techniques and customize metadata for a multilingual audience Additional course details: Nexus Humans B6252 IBM Cognos Framework Manager: Design Metadata Models v11.1.x 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 B6252 IBM Cognos Framework Manager: Design Metadata Models v11.1.x 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 geared for Python-experienced attendees who wish to be equipped with the skills you need to use pandas to ensure the veracity of your data, visualize it for effective decision-making, and reliably reproduce analyses across multiple datasets. Overview Working in a hands-on learning environment, guided by our expert team, attendees will learn to: Understand how data analysts and scientists gather and analyze data Perform data analysis and data wrangling using Python Combine, group, and aggregate data from multiple sources Create data visualizations with pandas, matplotlib, and seaborn Apply machine learning (ML) algorithms to identify patterns and make predictions Use Python data science libraries to analyze real-world datasets Use pandas to solve common data representation and analysis problems Build Python scripts, modules, and packages for reusable analysis code Perform efficient data analysis and manipulation tasks using pandas Apply pandas to different real-world domains with the help of step-by-step demonstrations Get accustomed to using pandas as an effective data exploration tool. Data analysis has become a necessary skill in a variety of domains where knowing how to work with data and extract insights can generate significant value. Geared for data team members with incoming Python scripting experience, Hands-On Data Analysis with Pandas will show you how to analyze your data, get started with machine learning, and work effectively with Python libraries often used for data science, such as pandas, NumPy, matplotlib, seaborn, and scikit-learn. Using real-world datasets, you will learn how to use the powerful pandas library to perform data wrangling to reshape, clean, and aggregate your data. Then, you will be able to conduct exploratory data analysis by calculating summary statistics and visualizing the data to find patterns. In the concluding lessons, you will explore some applications of anomaly detection, regression, clustering, and classification using scikit-learn to make predictions based on past data. Students will leave the course armed with the skills required to use pandas to ensure the veracity of their data, visualize it for effective decision-making, and reliably reproduce analyses across multiple datasets. Introduction to Data Analysis Fundamentals of data analysis Statistical foundations Setting up a virtual environment Working with Pandas DataFrames Pandas data structures Bringing data into a pandas DataFrame Inspecting a DataFrame object Grabbing subsets of the data Adding and removing data Data Wrangling with Pandas What is data wrangling? Collecting temperature data Cleaning up the data Restructuring the data Handling duplicate, missing, or invalid data Aggregating Pandas DataFrames Database-style operations on DataFrames DataFrame operations Aggregations with pandas and numpy Time series Visualizing Data with Pandas and Matplotlib An introduction to matplotlib Plotting with pandas The pandas.plotting subpackage Plotting with Seaborn and Customization Techniques Utilizing seaborn for advanced plotting Formatting Customizing visualizations Financial Analysis - Bitcoin and the Stock Market Building a Python package Data extraction with pandas Exploratory data analysis Technical analysis of financial instruments Modeling performance Rule-Based Anomaly Detection Simulating login attempts Exploratory data analysis Rule-based anomaly detection Getting Started with Machine Learning in Python Learning the lingo Exploratory data analysis Preprocessing data Clustering Regression Classification Making Better Predictions - Optimizing Models Hyperparameter tuning with grid search Feature engineering Ensemble methods Inspecting classification prediction confidence Addressing class imbalance Regularization Machine Learning Anomaly Detection Exploring the data Unsupervised methods Supervised methods Online learning The Road Ahead Data resources Practicing working with data Python practice

There is a lot to learn in Power BI, this course takes a comprehensive look at the fundamentals of analysing data and includes a balanced look at the four main components that make up Power BI Desktop: Report view, Data view, Model view, and the Power Query Editor. It also demonstrates how to utilise the online Power BI service. It looks at authoring tools that enable you to connect to and transform data from a variety of sources, allowing you to produce detailed reports through a range of visualisations, in an interactive and dynamic way. It also includes a detailed look at formulas by writing both M functions in Power Query, and DAX functions in Desktop view. This knowledge will allow you to take your reports to the next level. The aim of this course is to provide a complete introduction to understanding the Power BI analysis process, by working hands-on with examples that will equip you with the necessary skills to start applying your learning straight away. 1 Getting Started The Power BI ecosystem Opening Power BI Desktop Power BI's four views Introduction to Dashboards 2 Importing Files Importing data sources Importing an Excel file Importing a CSV file Importing a database Connect to an SQL Server Database Import vs. Direct Query Importing from the web Importing a folder of files Managing file connections 3 Shape Data in the Query Editor The process of shaping data Managing data types Keeping and removing rows Add a custom column Appending tables together Hiding queries in reports Fixing error issues Basic maths operations 4 The Data Model Table relationships Relationship properties 5 Merge Queries Table join kinds Merging tables 6 Inserting Dashboard Visuals Things to keep in mind Inserting maps Formatting Maps Inserting charts Formatting Charts Inserting a tree map Inserting a table, matrix, and card Controlling number formats About report themes Highlighting key points Filter reports with slicers Sync slicers across dashboards Custom web visuals 7 Publish and share Reports Publishing to Power BI service Editing online reports Pinning visuals to a dashboard What is Q&A? Sharing dashboards Exporting reports to PowerPoint Exporting reports as PDF files 8 The Power Query Editor Fill data up and down Split column by delimiter Add a conditional column More custom columns Merging columns 9 The M Functions Inserting text functions Insert an IF function Create a query group 10 Pivoting Tables Pivot a table Pivot and append tables Pivot but don't aggregate Unpivot tables Append mismatched headers 11 Data Modelling Expanded Understanding relationships Mark a date table 12 DAX New Columns New columns and measures New column calculations Insert a SWITCH function 13 Introduction to DAX Measures Common measure functions Insert a SUM function Insert a COUNTROWS function Insert a DISTINCTCOUNT function Insert a DIVIDE function DAX rules 14 The CALCULATE Measure The syntax of CALCULATE Insert a CALCULATE function Control field summarisation Things of note 15 The SUMX measure X iterator functions Anatomy of SUMX Insert a SUMX function When to use X functions 16 Time Intelligence Measures Importance of a calendar table Insert a TOTALYTD function Change financial year end date Comparing historical data Insert a DATEADD function 17 Hierarchies and Groups Mine data using hierarchies Compare data in groups

This course starts with data transformation strategies, exploring capabilities in the Power Query Editor, and data-cleansing practices. It looks at the Advanced Query Editor to view the M language code. This course focuses on advanced DAX measures that include filtering conditions, with a deep dive into time intelligence measures. Like the M query language, DAX is a rich functional language that supports variables and expression references. This course also looks at the creation of dynamic dashboards and incorporates a range of visualisations available in Power BI Desktop and online in the AppSource. The course finishes with a look at setting up end user level security in tables. 1 The query editor Split by row delimiter AddDays to determine deadlines Advanced query editor 2 Fuzzy matching joins Matching inconsistencies by percentage Matching with transformation table 3 Logical column functions Logical functions IF, AND, OR Using multiple conditions Including FIND in functions 4 Editing DAX measures Make DAX easier to read Add comments to a measure Using quick measures 5 The anatomy of CALCULATE Understanding CALCULATE context filters Adding context to CALCULATE with FILTER Using CALCULATE with a threshold 6 The ALL measure Anatomy of ALL Create an ALL measure Using ALL as a filter Use ALL for percentage 7 DAX iterators Anatomy of iterators A closer look at SUMX Using RELATED in SUMX Create a RANKX RANKX with ALL 8 Date and time functions Overview of functions Create a DATEDIFF function 9 Time intelligent measures Compare historical monthly data Create a DATEADD measure Creating cumulative totals Creating cumulative measures Visualising cumulative totals 10 Visualisations in-depth Utilising report themes Create a heatmap Comparing proportions View trends with sparklines Group numbers using bins Setting up a histogram 11 Comparing variables Visualising trendlines as KPI Forecasting with trendlines Creating a scatter plot Creating dynamic labels Customised visualisation tooltips Export reports to SharePoint 12 User level security Setting up row level security Testing user security

This course starts with the basics then moves seamlessly to an intermediate level. It includes a comprehensive yet balanced look at the four main components that make up Power BI Desktop: Report view, Data view, Model view, and the Power Query Editor. It also demonstrates how to use the online Power BI service. It looks at authoring tools that enables you to connect to and transform data from a variety of sources, allowing you to produce dynamic reports using a library of visualisations. Once you have those reports, the course looks at the seamless process of sharing those with your colleagues by publishing to the online Power BI service. The aim of this course is to provide a strong understanding of the Power BI analysis process, by working with real-world examples that will equip you with the necessary skills to start applying your knowledge straight away. 1 Getting started The Power BI process Launching Power BI Desktop The four views of Power BI Dashboard visuals 2 Connecting to files Connect to data sources Connect to an Excel file Connect to a CSV file Connect to a database Import vs. DirectQuery Connect to a web source Create a data table 3 Transforming data The process of cleaning data Column data types Remove rows with filters Add a custom column Append data to a table Fix error issues Basic maths operations 4 Build a data model Table relationships Manage table relationships 5 Merge queries Table join kinds Merging tables 6 Create report visualisations Creating map visuals Formatting maps Creating chart visuals Formatting chart Tables, matrixes, and cards Control formatting with themes Filter reports with slicers Reports for mobile devices Custom online visuals Export report data to Excel 7 The power query editor Fill data up and down Split columns by delimiter Add conditional columns Merging columns 8 The M formula Creating M functions Create an IF function Create a query group 9 Pivot and unpivot tables Pivot tables in the query editor Pivot and append tables Pivot but don't summarise Unpivot tables Append mismatched headers 10 Data modelling revisited Data model relationships Mark a calendar as a date table 11 Introduction to calculated columns New columns vs. measures Creating a new column calculation The SWITCH function 12 Introduction to DAX measures Common measure categories The SUM measure Adding measures to visuals COUNTROWS and DISINCTCOUNT functions DAX rules 13 The CALCULATE measure The syntax of CALCULATE Things of note about CALCULATE 14 The SUMX measure The SUMX measure X iterator functions Anatomy of SUMX 15 Introduction to time intelligence Importance of a calendar table A special lookup table The TOTALYTD measure Change year end in TOTALYTD 16 Hierarchy, groups and formatting Create a hierarchy to drill data Compare data in groups Add conditional formatting 17 Share reports on the web Publish to the BI online service Get quick insights Upload reports from BI service Exporting report data What is Q&A? Sharing your reports 18 Apply your learning Post training recap lesson

Duration 2 Days 12 CPD hours This course is intended for This course is intended for system and network administrators or operators responsible for the installation, setup, configuration, and administration of the BIG-IQ system or management of BIG-IP devices and F5 products running on those devices. This course uses lectures and hands-on exercises to give participants real-time experience in configuring and using the BIG-IQ© product. Students are introduced to BIG-IQ, its interface, and its various functionality. We first look at administering and operating the BIG-IQ system itself, then detail how it is used to remotely manage BIG-IP devices running BIG-IP Local Traffic Manager (LTM). We then look configuring a BIG-IQ Data Collection Device (DCD) system and see how it is used for the remote storage and examination of BIG-IP log events and statistics. Module 1: BIG-IQ Overview BIG-IQ Centralized Management BIG-IQ Components BIG-IQ Core Functionality REST API BIG-IQ Data Collection Device (DCD) BIG-IP Cloud Edition (CE) Setting up the BIG-IQ System Module 2: Administering the BIG-IQ System Controlling Access to the BIG-IQ Creating, Authenticating, Configuring Users Backups Local Host Settings Configuring DNS, NTP, and SMTP Monitoring BIG-IQ, DCD, and BIG-IP Events with Alerts Monitoring BIG-IQ with iHealth Post Installation Issues; Licensing, Changing Management IP, Master Key, Restoring Backups Module 3: Managing BIG-IP LTM Devices BIG-IP LTM Device Discovery BIG-IP Device Backup Deploying to BIG-IP Devices Deployment and Deployment Logs Configuration Snapshots Managing BIG-IP Certificates Managing BIG-IP Licenses Monitoring BIG-IP Devices with iHealth Management of QKView Reports from Managed BIG-IP Devices Module 4: Setting Up the BIG-IQ Data Collection Device Custom Roles Types and Groups Setting up User Accounts with custom roles and privileges Managing BIG-IP DSC Discovery and management of BIG-IP Device Clusters (DSC) with BIG-IQ Administering BIG-IQ High Availability Configuration and management of BIG-IQ systems in a High Availability pair

Duration 2 Days 12 CPD hours This course is intended for This course is designed for professionals in a variety of job roles who are currently using desktop or web-based data management tools such as Microsoft Excel or SQL Server reporting services to perform numerical or general data analysis. They are responsible for connecting to cloud-based data sources, as well as shaping and combining data for the purpose of analysis. They are also looking for alternative ways to analyze business data, visualize insights, and share those insights with peers across the enterprise. This includes capturing and reporting on data to peers, executives, and clients. Overview In this course, you will analyze data with Microsoft Power BI. You will: Analyze data with self-service BI. Connect to data sources. Perform data cleaning, profiling, and shaping. Visualize data with Power BI. Enhance data analysis by adding and customizing visual elements. Model data with calculations. Create interactive visualizations. As technology progresses and becomes more interwoven with our businesses and lives, more data is collected about business and personal activities. This era of 'big data' is a direct result of the popularity and growth of cloud computing, which provides an abundance of computational power and storage, allowing organizations of all sorts to capture and store data. Leveraging that data effectively can provide timely insights and competitive advantages. Creating data-backed visualizations is key for data scientists, or any professional, to explore, analyze, and report insights and trends from data. Microsoft© Power BI© software is designed for this purpose. Power BI was built to connect to a wide range of data sources, and it enables users to quickly create visualizations of connected data to gain insights, show trends, and create reports. Power BI's data connection capabilities and visualization features go far beyond those that can be found in spreadsheets, enabling users to create compelling and interactive worksheets, dashboards, and stories that bring data to life and turn data into thoughtful action. Analyzing Data with Self-Service BI Topic A: Data Analysis and Visualization for Business Intelligence Topic B: Self-Service BI with Microsoft Power BI Connecting to Data Sources Topic A: Create Data Connections Topic B: Configure and Manage Data Relationships Topic C: Save Files in Power BI Performing Data Cleaning, Profiling, and Shaping Topic A: Clean, Transform, and Load Data with the Query Editor Topic B: Profile Data with the Query Editor Topic C: Shape Data with the Query Editor Topic D: Combine and Manage Data Rows Visualizing Data with Power BI Topic A: Create Visualizations in Power BI Topic B: Chart Data in Power BI Enhancing Data Analysis Topic A: Customize Visuals and Pages Topic B: Incorporate Tooltips Modeling Data with Calculations Topic A: Create Calculations with Data Analysis Expressions (DAX) Topic B: Create Calculated Measures and Conditional Columns Creating Interactive Visualizations Topic A: Create and Manage Data Hierarchies Topic B: Filter and Slice Reports Topic C: Create Dashboards Additional course details: Nexus Humans Microsoft Power BI: Data Analysis Practitioner (Second Edition) (v1.3) 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 Microsoft Power BI: Data Analysis Practitioner (Second Edition) (v1.3) 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 2 Days 12 CPD hours This course is intended for This is an Intermediate PowerBI course geared for experienced users who wish to leverage the tool's more advanced capabilities Overview This course is about 50% hands-on lab and 50% lecture, designed to train attendees in essential PowerBI data handling functions and reporting skills, coupling the most current, effective techniques with the soundest practices. Attendees of this course will gain practical examples from the experienced instructor who has deployed and configured Power BI reporting in a wide variety of businesses. Working in a hands-on learning environment led by our expert facilitator, students will learn how to: Create Advanced Power BI Reports Advanced understanding of the data schemas and extracting data Perform advanced transformations of data or any data schema Utilize time-phased data in the creation of complex analyses Create new measures using DAX Filter data using row-level security Create and deploy content packs Use Power BI to integrate with line-of-business applications Next Level Power BI for Experienced Users is a two day, course that provides attendees already experienced with Microsoft Power BI basics with a hands-on exploration of intermediate and beyond level features. This course is geared for attendees ready to learn the advanced techniques that you, your business analysts, and your stakeholders need to create complex information from projects, program, and portfolio reporting to utilizing time-phased data and, potentially, data from your enterprise?s other line-of-business tools. Get Project Online Data Select and mine relevant tables with ODATA Advanced ODATA data mining Importing other data formats Advanced Editing of data queries Advanced Data Transformations Managing table relationships Creating & using data hierarchies Creating custom columns and measures and metrics for filtering and reporting Creating Power BI Reports Using advanced visualizations Configuring drill-down Modifying visual interactions Importing and creating custom visuals Configure Power BI Security Creating Dashboard and row-level security Utilizing Filtering using row-level security Publishing Reports and Dashboards Building Mobile Reporting Creating and deploying content packs Configuring natural language query