124 Courses in Cardiff delivered Live Online

Python Data Analytics with Python using Numpy, Pandas, Dataframes. Most attendees are in-work Data Professional. Private individuals are very welcome. Our Style: Hands-on, Practical Location: Online, Instructor-led

Duration 3 Days 18 CPD hours This course is intended for This course is intended for system administrators, network administrators and application developers responsible for the customization of traffic flow through a BIG-IP system. This course provides networking professionals a functional understanding of iRules development. The course builds on the foundation of the Administering BIG-IP or Configuring LTM course, demonstrating how to logically plan and write iRules to help monitor and manage common tasks involved with processing traffic on the BIG-IP system. Extensive course labs consist of writing, applying and evaluating the effect of iRules on local traffic. This hands-on course includes lectures, labs, and discussions. Module 1: Setting Up the BIG-IP System Introducing the BIG-IP System Initially Setting Up the BIG-IP System Archiving the BIG-IP System Configuration Leveraging F5 Support Resources and Tools Module 2: Getting Started with iRules Customizing Application Delivery with iRules Triggering an iRule Leveraging the DevCentral Ecosystem Creating and Deploying iRules Module 3: Exploring iRule Elements Introducing iRule Constructs Understanding iRule Events and Event Context Working with iRule Commands Logging from an iRule Using SYSLOG-NG (LOG Command) Working with User-Defined Variables Working with Operators and Data Types Working with Conditional Control Structures (IF and SWITCH) Incorporating Best Practices in iRules Module 4: Developing and Troubleshooting iRules Mastering Whitespace and Special Symbols Grouping Strings Developing and Troubleshooting Tips Using Fiddler to Test and Troubleshoot iRules Module 5: Optimizing iRule Execution Understanding the Need for Efficiency Measure iRule Runtime Efficiency Using Timing Statistics Modularizing iRules for Administrative Efficiency Using Procedures to Modularize Code Optimizing Logging Using High-Speed Logging Commands in an iRule Implementing Other Efficiencies Using Looping Control Structures (WHILE, FOR, FOREACH Commands) Module 6: Securing Web Applications with iRules Integrating iRules into Web Application Defense Mitigating HTTP Version Attacks Mitigating Path Traversal Attacks Using iRules to Defends Against Cross-Site Request Forgery (CSRF) Mitigating HTTP Method Vulnerabilities Securing HTTP Cookies with iRules Adding HTTP Security Headers Removing Undesirable HTTP Headers Module 7: Working with Numbers and Strings Understanding Number Forms and Notation Working with Strings (STRING and SCAN Commands) Combining Strings (Adjacent Variables, CONCAT and APPEND Commands) Using iRule String Parsing Functions (FINDSTR, GETFIELD, and SUBSTR Commands) Module 8: Processing the HTTP Payload Reviewing HTTP Headers and Commands Accessing and Manipulating HTTP Headers (HTTP::header Commands) Other HTTP commands (HTTP::host, HTTP::status, HTTP::is_keepalive, HTTP::method, HTTP::version, HTTP::redirect, HTTP::respond, HTTP::uri) Parsing the HTTP URI (URI::path, URI::basename, URI::query) Parsing Cookies with HTTP::cookie Selectively Compressing HTTP Data (COMPRESS Command) Module 9: Working with iFiles and Data Groups Working with iFiles Introducing Data Groups Working with Old Format Data Groups (MATCHCLASS, FINDCLASS) Working with New Format Data Groups (CLASS MATCH, CLASS SEARCH) Module 10: Using iRules with Universal Persistence, Stream, and Statistics Profiles Implementing Universal Persistence (PERSIST UIE Command) Working with the Stream Profile (STREAM Command) Collecting Statistics Using a Statistics Profile (STATS Command) Collecting Statistics Using iStats (ISTATS Command) Module 11: Incorporating Advanced Variables Reviewing the Local Variable Namespace Working with Arrays (ARRAY Command) Using Static and Global Variables Using the Session Table (TABLE Command) Processing Session Table Subtables Counting ?Things? Using the Session Table

Course Objectives The goal of this course is to provide you with the knowledge required to use more advanced functions and formulas and work with various tools to analyse and present data in spreadsheets, such as sorting, filtering, applying conditional formatting and charting the data. ' Customer Feedback Really useful and engaging course. Learnt a lot that will be very beneficial in my job. Trainer was great. Kelly Moreley - TACT Very happy with the course. Worked as a good refresher from what I knew already and enhanced my knowledge further in formulas + vlookup and shortcut keys. Jenny Price - Acer 1 year email support service Take a look at the consistent excellent feedback from our corporate clients visiting our site ms-officetraining co uk With more than 20 years experience, we deliver courses on all levels of the Desktop version of Microsoft Office and Office 365; ranging from Beginner, Intermediate, Advanced to the VBA level. Our trainers are Microsoft certified professionals with a proven track record with several years experience in delivering public, one to one, tailored and bespoke courses. Tailored training courses: In, in company training, you can choose to run the course exactly as they are outlined by us or we can customise it so that it meets your specific needs. A tailored or bespoke course will follow the standard outline but may be adapted to your specific organisational needs. Recap on Excel formulas and calculations Overview of formulas in Excel Relative, Absolute and Mixed cell references Group editing worksheets Autofill and Flash Fill Changing Excel’s environment Options Changing the default number of sheets Creating an Autofill Custom List Adding tools to the Quick Access Toolbar Mastering Excel Tables Introducing Excel Tables Formatting a Table Creating Calculated Columns Using Slicers to filter your data Using Totals to get statistics out of your data Removing duplicates Converting Tables back to normal Ranges Using names Ranges In Excel formulas As a way of navigating through the workbook Advanced Formulas Simple IF examples Using IF to check if a cell is blank Nested IFs VLOOKUP HLOOKUP Text Functions Date Functions Conditional formatting Apply Conditional Formatting Customising Conditional Formatting Using Icons in Conditional Formatting Using Formulas to conditionally format cells Linking spreadsheets and workbooks Making a reference to another worksheet Making a reference to another workbook Editing links Troubleshooting links Analysing databases Quick analysis Sorting a database Apply filters to a database Advance filter Sorting and Filtering by Conditional Formats Charts Analyse trends in data using Sparklines Creating charts from start to finish Exploring the different Chart Types Apply Chart Styles Formatting Chart Elements Filtering Charts by Series or Categories Adding a Trendline to a Chart Create a Chart Template Attaching security to a spreadsheet and workbook Protect Cells Protect Structure of worksheets Protect a Workbook by adding passwords Introduction to Pivot Tables What are Pivot Tables? Using recommended pivot tables to analyse your data Who is this course for? Who is this course for? For those who want to explore in more detail formulas and functions, data analysis and data presentation. Requirements Requirements Preferably, delegates would have attended the Excel Introduction course. Career path Career path Excel know-how can instantly increase your job prospects as well as your salary. 80 percent of job openings require spreadsheet and word-processing software skills Certificates Certificates Certificate of completion Digital certificate - Included

Duration 5 Days 30 CPD hours This course is intended for Data Warehouse AdministratorDatabase Administrators Overview Use the Oracle Database tuning methodology appropriate to the available toolsUtilize database advisors to proactively tune an Oracle Database InstanceUse the tools based on the Automatic Workload Repository to tune the databaseDiagnose and tune common SQL related performance problemsDiagnose and tune common Instance related performance problemsUse Enterprise Manager performance-related pages to monitor an Oracle DatabaseGain an understanding of the Oracle Database Cloud Service In the Oracle Database 12c: Performance Management and Tuning course, learn about the performance analysis and tuning tasks expected of a DBA: proactive management through built-in performance analysis features and tools, diagnosis and tuning of the Oracle Database instance components, and diagnosis and tuning of SQL-related performance issues. In this course, you will be introduced to Oracle Database Cloud Service. Introduction Course Objectives Course Organization Course Agenda Topics Not Included in the Course Who Tunes? What Does the DBA Tune? How to Tune Tuning Methodology Basic Tuning Diagnostics Performance Tuning Diagnostics Performance Tuning Tools Tuning Objectives Top Timed Events DB Time CPU and Wait Time Tuning Dimensions Time Model Dynamic Performance Views Using Automatic Workload Repository Automatic Workload Repository Overview Automatic Workload Repository Data Enterprise Manager Cloud Control and AWR Snapshots Reports Compare Periods Defining the Scope of Performance Issues Defining the Problem Limiting the Scope Setting the Priority Top SQL Reports Common Tuning Problems Tuning During the Life Cycle ADDM Tuning Session Performance Versus Business Requirements Using Metrics and Alerts Metrics and Alerts Overview Limitation of Base Statistics Benefits of Metrics Viewing Metric History Information Viewing Histograms Server-Generated Alerts Setting Thresholds Metrics and Alerts Views Using Baselines Comparative Performance Analysis with AWR Baselines Automatic Workload Repository Baselines Moving Window Baseline Baselines in Performance Page Settings Baseline Templates AWR Baseslines Creating AWR Baselines Managing Baselines with PL/SQL Using AWR-Based Tools Automatic Maintenance Tasks ADDM Performance Monitoring Using Compare Periods ADDM Active Session History New or Enhanced Automatic Workload Repository Views Emergency Monitoring Real-time ADDM Real-Time Database Operation Monitoring Overview Use Cases Defining a Database Operation Scope of a Composite Database Operation Database Operation Concepts Identifying a Database Operation Enabling Monitoring of Database Operations Identifying, Starting, and Completing a Database Operation Monitoring Applications What is a Service? Service Attributes Service Types Creating Services Managing Services in a Single-Instance Environment Where are Services Used? Using Services with Client Applications Services and Pluggable Databases Identifying Problem SQL Statements SQL Statement Processing Phases Role of the Oracle Optimizer Identifying Bad SQL Top SQL Reports SQL Monitoring What is an Execution Plan? Methods for Viewing Execution Plans Uses of Execution Plans Influencing the Optimizer Functions of the Query Optimizer Selectivity Cardinality and Cost Changing Optimizer Behavior Optimizer Statistics Extended Statistics Controlling the Behavior of the Optimizer with Parameters Enabling Query Optimizer Features Reducing the Cost of SQL Operations Reducing the Cost Index Maintenance SQL Access Advisor Table Maintenance for Performance Table Reorganization Methods Space Management Extent Management Data Storage Using SQL Performance Analyzer Real Application Testing: Overview Real Application Testing: Use Cases SQL Performance Analyzer: Process Capturing the SQL Workload Creating a SQL Performance Analyzer Task SQL Performance Analyzer: Tasks Parameter Change SQL Performance Analyzer Task Page SQL Performance Management Maintaining SQL Performance Maintaining Optimizer Statistics Automated Maintenance Tasks Statistic Gathering Options Setting Statistic Preferences Restore Statistics Deferred Statistics Publishing Automatic SQL Tuning Using Database Replay Using Database Replay The Big Picture System Architecture Capture Considerations Replay Considerations: Preparation Replay Considerations Replay Options Replay Analysis Tuning the Shared Pool Shared Pool Architecture Shared Pool Operation The Library Cache Latch and Mutex Diagnostic Tools for Tuning the Shared Pool Avoiding Hard Parses Reducing the Cost of Soft Parses Sizing the Shared Pool Tuning the Buffer Cache Oracle Database Architecture: Buffer Cache Buffer Cache: Highlights Database Buffers Buffer Hash Table for Lookups Working Sets Buffer Cache Tuning Goals and Techniques Buffer Cache Performance Symptoms Buffer Cache Performance Solutions Tuning PGA and Temporary Space SQL Memory Usage Performance Impact Automatic PGA Memory SQL Memory Manager Configuring Automatic PGA Memory Setting PGA_AGGREGATE_TARGET Initially Limiting the size of the Program Global Area (PGA) SQL Memory Usage Automatic Memory Oracle Database Architecture Dynamic SGA Granule Memory Advisories Manually Adding Granules to Components Increasing the Size of an SGA Component Automatic Shared Memory Management: Overview SGA Sizing Parameters: Overview Performance Tuning Summary with Waits Commonly Observed Wait Events Additional Statistics Top 10 Mistakes Found in Customer Systems Symptoms Oracle Database Cloud Service: Overview Database as a Service Architecture, Features and Tooling Software Editions: Included Database Options and Management Packs Accessing the Oracle Database Cloud Service Console Automated Database Provisioning Managing the Compute Node Associated With a Database Deployment Managing Network Access to Database as a Service Scaling a Database Deployment Performance Management in the Database Cloud Environment Performance Monitoring and Tuning What Can be Tuned in a DBCS Environment?

Practical MySQL Course Intermediate, to leave you fully conversant with queries, DML and DDL statements. Hands-on, Practical MySQL Course Intermediate. PCWorkshops MySQL Course Intermediate Certificate. Max 4 people per course, we keep it personalised.

Duration 2 Days 12 CPD hours This course is intended for Audience: Data Scientists, Software Developers, IT Architects, and Technical Managers. Participants should have the general knowledge of statistics and programming Also familiar with Python Overview ? NumPy, pandas, Matplotlib, scikit-learn ? Python REPLs ? Jupyter Notebooks ? Data analytics life-cycle phases ? Data repairing and normalizing ? Data aggregation and grouping ? Data visualization ? Data science algorithms for supervised and unsupervised machine learning Covers theoretical and technical aspects of using Python in Applied Data Science projects and Data Logistics use cases. Python for Data Science ? Using Modules ? Listing Methods in a Module ? Creating Your Own Modules ? List Comprehension ? Dictionary Comprehension ? String Comprehension ? Python 2 vs Python 3 ? Sets (Python 3+) ? Python Idioms ? Python Data Science ?Ecosystem? ? NumPy ? NumPy Arrays ? NumPy Idioms ? pandas ? Data Wrangling with pandas' DataFrame ? SciPy ? Scikit-learn ? SciPy or scikit-learn? ? Matplotlib ? Python vs R ? Python on Apache Spark ? Python Dev Tools and REPLs ? Anaconda ? IPython ? Visual Studio Code ? Jupyter ? Jupyter Basic Commands ? Summary Applied Data Science ? What is Data Science? ? Data Science Ecosystem ? Data Mining vs. Data Science ? Business Analytics vs. Data Science ? Data Science, Machine Learning, AI? ? Who is a Data Scientist? ? Data Science Skill Sets Venn Diagram ? Data Scientists at Work ? Examples of Data Science Projects ? An Example of a Data Product ? Applied Data Science at Google ? Data Science Gotchas ? Summary Data Analytics Life-cycle Phases ? Big Data Analytics Pipeline ? Data Discovery Phase ? Data Harvesting Phase ? Data Priming Phase ? Data Logistics and Data Governance ? Exploratory Data Analysis ? Model Planning Phase ? Model Building Phase ? Communicating the Results ? Production Roll-out ? Summary Repairing and Normalizing Data ? Repairing and Normalizing Data ? Dealing with the Missing Data ? Sample Data Set ? Getting Info on Null Data ? Dropping a Column ? Interpolating Missing Data in pandas ? Replacing the Missing Values with the Mean Value ? Scaling (Normalizing) the Data ? Data Preprocessing with scikit-learn ? Scaling with the scale() Function ? The MinMaxScaler Object ? Summary Descriptive Statistics Computing Features in Python ? Descriptive Statistics ? Non-uniformity of a Probability Distribution ? Using NumPy for Calculating Descriptive Statistics Measures ? Finding Min and Max in NumPy ? Using pandas for Calculating Descriptive Statistics Measures ? Correlation ? Regression and Correlation ? Covariance ? Getting Pairwise Correlation and Covariance Measures ? Finding Min and Max in pandas DataFrame ? Summary Data Aggregation and Grouping ? Data Aggregation and Grouping ? Sample Data Set ? The pandas.core.groupby.SeriesGroupBy Object ? Grouping by Two or More Columns ? Emulating the SQL's WHERE Clause ? The Pivot Tables ? Cross-Tabulation ? Summary Data Visualization with matplotlib ? Data Visualization ? What is matplotlib? ? Getting Started with matplotlib ? The Plotting Window ? The Figure Options ? The matplotlib.pyplot.plot() Function ? The matplotlib.pyplot.bar() Function ? The matplotlib.pyplot.pie () Function ? Subplots ? Using the matplotlib.gridspec.GridSpec Object ? The matplotlib.pyplot.subplot() Function ? Hands-on Exercise ? Figures ? Saving Figures to File ? Visualization with pandas ? Working with matplotlib in Jupyter Notebooks ? Summary Data Science and ML Algorithms in scikit-learn ? Data Science, Machine Learning, AI? ? Types of Machine Learning ? Terminology: Features and Observations ? Continuous and Categorical Features (Variables) ? Terminology: Axis ? The scikit-learn Package ? scikit-learn Estimators ? Models, Estimators, and Predictors ? Common Distance Metrics ? The Euclidean Metric ? The LIBSVM format ? Scaling of the Features ? The Curse of Dimensionality ? Supervised vs Unsupervised Machine Learning ? Supervised Machine Learning Algorithms ? Unsupervised Machine Learning Algorithms ? Choose the Right Algorithm ? Life-cycles of Machine Learning Development ? Data Split for Training and Test Data Sets ? Data Splitting in scikit-learn ? Hands-on Exercise ? Classification Examples ? Classifying with k-Nearest Neighbors (SL) ? k-Nearest Neighbors Algorithm ? k-Nearest Neighbors Algorithm ? The Error Rate ? Hands-on Exercise ? Dimensionality Reduction ? The Advantages of Dimensionality Reduction ? Principal component analysis (PCA) ? Hands-on Exercise ? Data Blending ? Decision Trees (SL) ? Decision Tree Terminology ? Decision Tree Classification in Context of Information Theory ? Information Entropy Defined ? The Shannon Entropy Formula ? The Simplified Decision Tree Algorithm ? Using Decision Trees ? Random Forests ? SVM ? Naive Bayes Classifier (SL) ? Naive Bayesian Probabilistic Model in a Nutshell ? Bayes Formula ? Classification of Documents with Naive Bayes ? Unsupervised Learning Type: Clustering ? Clustering Examples ? k-Means Clustering (UL) ? k-Means Clustering in a Nutshell ? k-Means Characteristics ? Regression Analysis ? Simple Linear Regression Model ? Linear vs Non-Linear Regression ? Linear Regression Illustration ? Major Underlying Assumptions for Regression Analysis ? Least-Squares Method (LSM) ? Locally Weighted Linear Regression ? Regression Models in Excel ? Multiple Regression Analysis ? Logistic Regression ? Regression vs Classification ? Time-Series Analysis ? Decomposing Time-Series ? Summary Lab Exercises Lab 1 - Learning the Lab Environment Lab 2 - Using Jupyter Notebook Lab 3 - Repairing and Normalizing Data Lab 4 - Computing Descriptive Statistics Lab 5 - Data Grouping and Aggregation Lab 6 - Data Visualization with matplotlib Lab 7 - Data Splitting Lab 8 - k-Nearest Neighbors Algorithm Lab 9 - The k-means Algorithm Lab 10 - The Random Forest Algorithm

Duration 4 Days 24 CPD hours This course is intended for The information protection administrator translates an organization?s risk and compliance requirements into technical implementation. They are responsible for implementing and managing solutions for content classification, data loss prevention (DLP), information protection, data lifecycle management, records management, privacy, risk, and compliance. They also work with other roles that are responsible for governance, data, and security to evaluate and develop policies to address an organization's risk reduction and compliance goals. This role assists workload administrators, business application owners, human resources departments, and legal stakeholders to implement technology solutions that support the necessary policies and controls. Learn how to protect information in your Microsoft 365 deployment. This course focuses on data lifecycle management and information protection and compliance within your organization. The course covers implementation of data loss prevention policies, sensitive information types, sensitivity labels, data retention policies, Microsoft Purview Message Encryption, audit, eDiscovery, and insider risk among other related topics. The course helps learners prepare for the Microsoft Information Protection Administrator exam (SC-400). Prerequisites Foundational knowledge of Microsoft security and compliance technologies. Basic knowledge of information protection concepts. Understanding of cloud computing concepts. Understanding of Microsoft 365 products and services. 1 - Introduction to information protection and data lifecycle management in Microsoft Purview Know your data Protect your data Prevent data loss Govern your data 2 - Classify data for protection and governance Data classification overview Classify data using sensitive information types Classify data using trainable classifiers Review sensitive information and label usage Explore labeled and sensitive content Understand activities related to your data 3 - Create and manage sensitive information types Compare built-in versus custom sensitive information types Create and manage custom sensitive information types Describe custom sensitive information types with exact data match Implement document fingerprinting Create keyword dictionary 4 - Understand Microsoft 365 encryption Learn how Microsoft 365 data is encrypted at rest Understand service encryption in Microsoft Purview Explore customer key management using Customer Key Learn how data is encrypted in-transit 5 - Deploy Microsoft Purview Message Encryption Implement Microsoft Purview Message Encryption Implement Microsoft Purview Advanced Message Encryption Use Microsoft Purview Message Encryption templates in mail flow rules 6 - Protect information in Microsoft Purview Information protection overview Configure sensitivity labels Configure sensitivity label policies Configure auto-labeling policies Manage, monitor, and remediate information protection 7 - Apply and manage sensitivity labels Apply sensitivity labels to Microsoft Teams, Microsoft 365 groups, and SharePoint sites Plan on-premises labeling Configure on-premises labeling for the Unified Labeling Scanner Apply protections and restrictions to email and files Monitor label performance using label analytics 8 - Prevent data loss in Microsoft Purview Data loss prevention overview Identify content to protect Define policy settings for your DLP policy Test and create your DLP policy Prepare Endpoint DLP Manage DLP alerts in the Microsoft Purview compliance portal View data loss prevention reports Implement the Microsoft Purview Extension 9 - Configure DLP policies for Microsoft Defender for Cloud Apps and Power Platform Configure data loss prevention policies for Power Platform Integrate data loss prevention in Microsoft Defender for Cloud Apps Configure policies in Microsoft Defender for Cloud Apps Manage data loss prevention violations in Microsoft Defender for Cloud Apps 10 - Manage data loss prevention policies and reports in Microsoft 365 Configure data loss prevention for policy precedence Implement data loss prevention policies in test mode Explain data loss prevention reporting capabilities Manage permissions for data loss prevention reports Manage and respond to data loss prevention policy violations 11 - Manage the data lifecycle in Microsoft Purview Data Lifecycle Management overview Configure retention policies Configure retention labels Configure manual retention label policies Configure auto-apply retention label policies Import data for Data Lifecycle Management Manage, monitor, and remediate Data Lifecycle Management 12 - Manage data retention in Microsoft 365 workloads Explain retention in Exchange Online Explain retention in SharePoint Online and OneDrive Explain retention in Microsoft Yammer Activate archive mailboxes in Microsoft Exchange Apply mailbox holds in Microsoft Exchange Recover content in Microsoft Exchange 13 - Manage records in Microsoft Purview Records management overview Import a file plan Configure retention labels Configure event driven retention Manage, monitor, and remediate records 14 - Explore compliance in Microsoft 365 Plan for security and compliance in Microsoft 365 Plan your beginning compliance tasks in Microsoft Purview Manage your compliance requirements with Compliance Manager Examine the Compliance Manager dashboard Analyze the Microsoft Compliance score 15 - Search for content in the Microsoft Purview compliance portal Explore Microsoft Purview eDiscovery solutions Create a content search View the search results and statistics Export the search results and search report Configure search permissions filtering Search for and delete email messages 16 - Manage Microsoft Purview eDiscovery (Standard) Explore Microsoft Purview eDiscovery solutions Implement Microsoft Purview eDiscovery (Standard) Create eDiscovery holds Search for content in a case Export content from a case Close, reopen, and delete a case 17 - Manage Microsoft Purview eDiscovery (Premium) Explore Microsoft Purview eDiscovery (Premium) Implement Microsoft Purview eDiscovery (Premium) Create and manage an eDiscovery (Premium) case Manage custodians and non-custodial data sources Analyze case content 18 - Manage Microsoft Purview Audit (Standard) Explore Microsoft Purview Audit solutions Implement Microsoft Purview Audit (Standard) Search the audit log Export, configure, and view audit log records Use audit log searching to investigate common support issues 19 - Prepare Microsoft Purview Communication Compliance Plan for communication compliance Identify and resolve communication compliance workflow Case study--Configure an offensive language policy Investigate and remediate communication compliance alerts 20 - Manage insider risk in Microsoft Purview Insider risk management overview Create and manage insider risk policies Investigate insider risk alerts Take action on insider risk alerts through cases Manage insider risk management forensic evidence Create insider risk management notice templates 21 - Implement Microsoft Purview Information Barriers Explore Microsoft Purview Information Barriers Configure information barriers in Microsoft Purview Examine information barriers in Microsoft Teams Examine information barriers in OneDrive Examine information barriers in SharePoint 22 - Manage regulatory and privacy requirements with Microsoft Priva Create and manage risk management policies Investigate and remediate risk management alerts Create rights requests Manage data estimate and retrieval for rights requests Review data from rights requests Get reports from rights requests 23 - Implement privileged access management Case study--Implementing privileged access management 24 - Manage Customer Lockbox Manage Customer Lockbox requests

Duration 4 Days 24 CPD hours This course is intended for The audience for this course is data professionals managing data and databases who want to learn about administering the data platform technologies that are available on Microsoft Azure. This course is also valuable for data architects and application developers who need to understand what technologies are available for the data platform with Azure and how to work with those technologies through applications. This course provides students with the knowledge and skills to administer a SQL Server database infrastructure for cloud, on-premises and hybrid relational databases and who work with the Microsoft PaaS relational database offerings. Additionally, it will be of use to individuals who develop applications that deliver content from SQL-based relational databases. Prerequisites In addition to their professional experience, students who take this training should have technical knowledge equivalent to the following courses: AZ-900T00 Microsoft Azure Fundamentals DP-900T00 Microsoft Azure Data Fundamentals 1 - Prepare to maintain SQL databases on Azure Describe Microsoft Intelligent Data Platform roles Understand SQL Server in an Azure virtual machine Design Azure SQL Database for cloud-native applications Explore Azure SQL Database Managed Instance 2 - Deploy IaaS solutions with Azure SQL Explain IaaS options to deploy SQL Server in Azure Understand hybrid scenarios Explore performance and security Explain high availability and disaster recovery options 3 - Deploy PaaS solutions with Azure SQL Explain PaaS options for deploying SQL Server in Azure Explore single SQL database Deploy SQL database elastic pool Understand SQL database hyperscale Examine SQL managed instance Describe SQL Edge 4 - Evaluate strategies for migrating to Azure SQL Understand compatibility level Understand Azure preview features Describe Azure database migration options 5 - Migrate SQL workloads to Azure SQL databases Choose the right SQL Server Instance option in Azure Migrate SQL Server to Azure SQL Database offline Migrate SQL Server to Azure SQL Database online Load and move data to Azure SQL Database 6 - Migrate SQL workloads to Azure Managed Instances Evaluate migration scenarios to SQL Database Managed Instance Migrate to SQL Database Managed Instance Load and Move data to SQL Database Managed Instance 7 - Configure database authentication and authorization Describe Active Directory and Azure Active Directory Describe authentication and identities Describe Security Principals Describe database and object permissions Identify authentication and authorization failures 8 - Protect data in-transit and at rest Explore Transparent Data Encryption Configure server and database firewall rules Explain object encryption and secure enclaves Enable encrypted connections Describe SQL injection Understand Azure Key Vault 9 - Implement compliance controls for sensitive data Explore data classification Explore server and database audit Implement Dynamic Data Masking Implement Row Level security Understand Microsoft Defender for SQL Explore Azure SQL Database Ledger Implement Azure Purview 10 - Describe performance monitoring Describe performance monitoring tools Describe critical performance metrics Establish baseline metrics Explore extended events Describe Azure SQL Insights Explore Query Performance Insight 11 - Configure SQL Server resources for optimal performance Explain how to optimize Azure storage for SQL Server virtual machines Describe virtual machine resizing Optimize database storage Control SQL Server resources 12 - Configure databases for optimal performance Explore database maintenance checks Describe database scoped configuration options Describe automatic tuning Describe intelligent query processing 13 - Explore query performance optimization Understand query plans Explain estimated and actual query plans Describe dynamic management views and functions Explore Query Store Identify problematic query plans Describe blocking and locking 14 - Evaluate performance improvements Describe wait statistics Tune and maintain indexes Understand query hints 15 - Explore performance-based design Describe normalization Choose appropriate data types Design indexes 16 - Automate deployment of database resources Describe deployment models in Azure Automate deployment by using Azure Resource Manager templates and Bicep Automate deployment by using PowerShell Automate deployment by using Azure CLI 17 - Create and manage SQL Agent jobs Create a SQL Server maintenance plan Describe task status notifications 18 - Manage Azure PaaS tasks using automation Explore Elastic jobs Understand Azure Automation Build an automation runbook Automate database workflows by using Logic Apps Monitor automated tasks 19 - Describe high availability and disaster recovery strategies Describe recovery time objective and recovery point objective Explore high availability and disaster recovery options Describe Azure high availability and disaster recovery features for Azure Virtual Machines Describe high availability and disaster recovery options for PaaS deployments Explore an IaaS high availability and disaster recovery solution Describe hybrid solutions 20 - Explore IaaS and PaaS solutions for high availability and disaster recovery Describe failover clusters in Windows Server Configure Always-on availability groups Describe temporal tables in Azure SQL Database Describe active geo-replication for Azure SQL Database Explore auto-failover groups for Azure SQL Database and Azure SQL Managed Instance 21 - Back up and restore databases Back up and restore SQL Server running on Azure virtual machines Back up a SQL Server virtual machine Back up and restore a database using Azure SQL Database Additional course details: Nexus Humans DP-300T00: Administering Microsoft Azure SQL Solutions 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-300T00: Administering Microsoft Azure SQL Solutions 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.

This course will enable you to bring value to the business by putting data science concepts into practice. Data is crucial for understanding where the business is and where it's headed. Not only can data reveal insights, but it can also inform - by guiding decisions and influencing day-to-day operations.

Become a Mental Health First Aid Champion Mental Health First Aid (MHFA) is an internationally recognised training course, which teaches people how to spot the signs and symptoms of mental ill health and to provide help on a first aid basis. This course is designed for people who want to promote and positively affect attitudes on mental health in the workplace.