4 Data Quality courses in London

Becoming a Data Quality Expert Data science is an exploding field with tremendous demand. Having high quality data is an absolute must for any business today and data informs every decision a business must make. But what if you have poor quality data? What if your company acquired another company and the data structure does not match? What if you have large gaps in the data you have vs. what you need?Imagine yourself as an IT project/program manager who has run many engagements for the business. You have great PM skills and you run your agenda with the precision of a Swiss watch. But you now have to run Data Quality for your organization. Can you just program manage this and be fine? What will be different about this than any other IT project?Wake-up call: a WHOLE LOT! You must acquire a lot of new skills and you must become a data expert as quickly as possible. I want to share with you my journey and experience. I have had to go from deeply technical in some IT areas, to project/program managing general IT projects, to gaining specialized skills in data quality. I will share with you my assessment, gap analysis and mitigation strategy that transformed me into a data quality expert.

A simple, logical and structured approach to help you successfully design and implement a Data Governance Framework.

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.

Project Risk Management: Virtual In-House Training Have you been surprised by unplanned events during your projects? Are you and your project team frequently fighting fires? Well, you are not alone. Uncertainty exists in any project environment. While it's impossible to predict project outcomes with 100% certainty, you can influence the outcome, avoid potential risks, and be ready to respond to challenges that arise. In this course, you'll gain the proper knowledge needed to identify, assess, plan for, and monitor risk in your projects. You'll learn how to set up and implement risk management processes, helping you to minimize uncertainty and achieve more consistent, predictable outcomes as a result. What You Will Learn You'll learn how to: Demonstrate to others how the risk management processes in A Guide to the Project Management Body of Knowledge (PMBOK® Guide) apply to your project's environment, especially for high-risk projects Adapt these processes for a particular high-risk project team's operating principles Explain the importance of using risk management best practices at single and enterprise project levels Lead an initiative to implement risk management best practices in your project environment Foundation Concepts Risk-related definitions The risk management process High-risk projects and project failures Classical failures in implementing risk management Plan Risk Management Project risk management and governance Risk management planning for high-risk projects High-risk variations on a risk management plan Identify Risk Adapting the risk identification process for high-risk projects Recognizing risks spontaneously Confirming and structuring risk events for treatment Wrapping up risk identification for high-risk projects Perform Qualitative Risk Analysis Adapting qualitative risk analysis for high-risk projects Accelerating risk analysis Clearing risk action Wrapping up qualitative risk analysis for the next level Perform Quantitative Risk Analysis Adapting quantitative risk analysis for high-risk projects Ensuring effective risk analyses with data quality assessments Building a foundation for quantitative risk analysis Using discrete quantitative tools Using continuous quantitative tools Wrapping up quantitative risk analysis for high-risk projects Plan Risk Responses Adapting risk response planning for high-risk projects Optimizing active risk response strategies Leveraging contingencies for high project performance Wrapping up risk response planning for high-risk projects Implement Risk Responses Implementing Risk Responses Process Executing Risk Response Plans Tools and Techniques Best Practices Continuous Risk Management Monitor Risks Adapting risk monitoring for high-risk projects Optimizing risk plan maintenance Weaving risk reassessment into the project's progress Maintaining a continuous 'vigil' in high-risk project environments

Duration 5 Days 30 CPD hours Overview Mining data Manipulating data Visualizing and reporting data Applying basic statistical methods Analyzing complex datasets while adhering to governance and quality standards throughout the entire data life cycle CompTIA Data+ is an early-career data analytics certification for professionals tasked with developing and promoting data-driven business decision-making. CompTIA Data+ gives you the confidence to bring data analysis to life. As the importance for data analytics grows, more job roles are required to set context and better communicate vital business intelligence. Collecting, analyzing, and reporting on data can drive priorities and lead business decision-making. 1 - Identifying Basic Concepts of Data Schemas Identify Relational and Non-Relational Databases Understand the Way We Use Tables, Primary Keys, and Normalization 2 - Understanding Different Data Systems Describe Types of Data Processing and Storage Systems Explain How Data Changes 3 - Understanding Types and Characteristics of Data Understand Types of Data Break Down the Field Data Types 4 - Comparing and Contrasting Different Data Structures, Formats, and Markup Languages Differentiate between Structured Data and Unstructured Data Recognize Different File Formats Understand the Different Code Languages Used for Data 5 - Explaining Data Integration and Collection Methods Understand the Processes of Extracting, Transforming, and Loading Data Explain API/Web Scraping and Other Collection Methods Collect and Use Public and Publicly-Available Data Use and Collect Survey Data 6 - Identifying Common Reasons for Cleansing and Profiling Data Learn to Profile Data Address Redundant, Duplicated, and Unnecessary Data Work with Missing Value Address Invalid Data Convert Data to Meet Specifications 7 - Executing Different Data Manipulation Techniques Manipulate Field Data and Create Variables Transpose and Append Data Query Data 8 - Explaining Common Techniques for Data Manipulation and Optimization Use Functions to Manipulate Data Use Common Techniques for Query Optimization 9 - Applying Descriptive Statistical Methods Use Measures of Central Tendency Use Measures of Dispersion Use Frequency and Percentages 10 - Describing Key Analysis Techniques Get Started with Analysis Recognize Types of Analysis 11 - Understanding the Use of Different Statistical Methods Understand the Importance of Statistical Tests Break Down the Hypothesis Test Understand Tests and Methods to Determine Relationships Between Variables 12 - Using the Appropriate Type of Visualization Use Basic Visuals Build Advanced Visuals Build Maps with Geographical Data Use Visuals to Tell a Story 13 - Expressing Business Requirements in a Report Format Consider Audience Needs When Developing a Report Describe Data Source Considerations For Reporting Describe Considerations for Delivering Reports and Dashboards Develop Reports or Dashboards Understand Ways to Sort and Filter Data 14 - Designing Components for Reports and Dashboards Design Elements for Reports and Dashboards Utilize Standard Elements Creating a Narrative and Other Written Elements Understand Deployment Considerations 15 - Understand Deployment Considerations Understand How Updates and Timing Affect Reporting Differentiate Between Types of Reports 16 - Summarizing the Importance of Data Governance Define Data Governance Understand Access Requirements and Policies Understand Security Requirements Understand Entity Relationship Requirements 17 - Applying Quality Control to Data Describe Characteristics, Rules, and Metrics of Data Quality Identify Reasons to Quality Check Data and Methods of Data Validation 18 - Explaining Master Data Management Concepts Explain the Basics of Master Data Management Describe Master Data Management Processes Additional course details: Nexus Humans CompTIA Data Plus (DA0-001) 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 CompTIA Data Plus (DA0-001) 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.

Thinking about learning more understanding the role of data within an organisation? As data becomes an important currency in the world and an enabler for the future, it is imperative that all organisations have a firm understanding of the data available to them and the power it can hold. The BCS Foundation Award in Understanding Data in your Organisation teaches the the terminology, principles, concepts and approaches used within data management, and the overall value of data to an organisation.

Get job ready with CompTIA's Data Analysis Certification. Live Classes - Career Guidance - Exam Included.

Project Risk Management: On-Demand Have you been surprised by unplanned events during your projects? Are you and your project team frequently fighting fires? Well, you are not alone. Uncertainty exists in any project environment. While it's impossible to predict project outcomes with 100% certainty, you can influence the outcome, avoid potential risks, and be ready to respond to challenges that arise. In this course, you'll gain the proper knowledge needed to identify, assess, plan for, and monitor risk in your projects. You'll learn how to set up and implement risk management processes, helping you to minimize uncertainty and achieve more consistent, predictable outcomes as a result. What You Will Learn You'll learn how to: Demonstrate to others how the risk management processes in A Guide to the Project Management Body of Knowledge (PMBOK® Guide) apply to your project's environment, especially for high-risk projects Adapt these processes for a particular high-risk project team's operating principles Explain the importance of using risk management best practices at single and enterprise project levels Lead an initiative to implement risk management best practices in your project environment Foundation Concepts Risk-related definitions The risk management process High-risk projects and project failures Classical failures in implementing risk management Plan Risk Management Project risk management and governance Risk management planning for high-risk projects High-risk variations on a risk management plan Identify Risk Adapting the risk identification process for high-risk projects Recognizing risks spontaneously Confirming and structuring risk events for treatment Wrapping up risk identification for high-risk projects Perform Qualitative Risk Analysis Adapting qualitative risk analysis for high-risk projects Accelerating risk analysis Clearing risk action Wrapping up qualitative risk analysis for the next level Perform Quantitative Risk Analysis Adapting quantitative risk analysis for high-risk projects Ensuring effective risk analyses with data quality assessments Building a foundation for quantitative risk analysis Using discrete quantitative tools Using continuous quantitative tools Wrapping up quantitative risk analysis for high-risk projects Plan Risk Responses Adapting risk response planning for high-risk projects Optimizing active risk response strategies Leveraging contingencies for high project performance Wrapping up risk response planning for high-risk projects Implement Risk Responses Implementing Risk Responses Process Executing Risk Response Plans Tools and Techniques Best Practices Continuous Risk Management Monitor Risks Adapting risk monitoring for high-risk projects Optimizing risk plan maintenance Weaving risk reassessment into the project's progress Maintaining a continuous 'vigil' in high-risk project environments

My popular 'Getting Started in Data Governance' course is making it's way across the pond!