407 Data Management courses in London delivered Online

Duration 4 Days 24 CPD hours This course is intended for Project administrators and ETL developers responsible for data extraction and transformation using DataStage. Overview Describe the uses of DataStage and the DataStage workflowDescribe the Information Server architecture and how DataStage fits within itDescribe the Information Server and DataStage deployment optionsUse the Information Server Web Console and the DataStage Administrator client to create DataStage users and to configure the DataStage environmentImport and export DataStage objects to a fileImport table definitions for sequential files and relational tablesDesign, compile, run, and monitor DataStage parallel jobsDesign jobs that read and write to sequential filesDescribe the DataStage parallel processing architectureDesign jobs that combine data using joins and lookupsDesign jobs that sort and aggregate dataImplement complex business logic using the DataStage Transformer stageDebug DataStage jobs using the DataStage PX Debugger This course enables the project administrators & developers to acquire the skills necessary to develop parallel jobs in DataStage. Students will learn to create parallel jobs that access sequential & relational data, and combine and transform the data. Course Outline Introduction to DataStage Deployment DataStage Administration Work with Metadata Create Parallel Jobs Access Sequential Data Partitioning and Collecting Algorithms Combine Data Group Processing Stages Transformer Stage Repository Functions Work with Relational Data Control Jobs

Acquire proficiency in Microsoft Power Apps fundamentals, including developing and distributing apps, as well as improving data management, app editing, and mobile integration abilities.

Duration 1 Days 6 CPD hours This course is intended for Certification Preparation for Administrator is designed for experienced Salesforce administrators who are planning to take the Salesforce Administrator Certification. Overview Understand the different exam objectives and their weighting on the exam Know which product areas to focus on to best prepare for your exam How to approach exam questions Additional resources available to help prepare for the exam Are you ready to take the next step in your career by becoming a Salesforce Certified Administrator? By covering the details around the exam objectives, this course will help hone your problem-solving skills and reinforce your knowledge of key topics. Instructors will present different administration and configuration scenarios tied to the exam objectives. Questions related to these scenarios will help prepare you to help prepare you for your exam. Introduction and OverviewSecurity and Record AccessStandard and Custom Objects Automation and ValidationData Management Reports and DashboardsPractice Test and DiscussionConclusion and Next Steps Additional course details: Nexus Humans Salesforce Certification Preparation for Administrator (CRT101) 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 Salesforce Certification Preparation for Administrator (CRT101) 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 Experienced DataStage developers seeking training in more advanced DataStage job techniques and who seek techniques for working with complex types of data resources. Overview Use Connector stages to read from and write to database tables Handle SQL errors in Connector stages Use Connector stages with multiple input links Use the File Connector stage to access Hadoop HDFS data Optimize jobs that write to database tables Use the Unstructured Data stage to extract data from Excel spreadsheets Use the Data Masking stage to mask sensitive data processed within a DataStage job Use the Hierarchical stage to parse, compose, and transform XML data Use the Schema Library Manager to import and manage XML schemas Use the Data Rules stage to validate fields of data within a DataStage job Create custom data rules for validating data Design a job that processes a star schema data warehouse with Type 1 and Type 2 slowly changing dimensions This course is designed to introduce you to advanced parallel job data processing techniques in DataStage v11.5. In this course you will develop data techniques for processing different types of complex data resources including relational data, unstructured data (Excel spreadsheets), and XML data. In addition, you will learn advanced techniques for processing data, including techniques for masking data and techniques for validating data using data rules. Finally, you will learn techniques for updating data in a star schema data warehouse using the DataStage SCD (Slowly Changing Dimensions) stage. Even if you are not working with all of these specific types of data, you will benefit from this course by learning advanced DataStage job design techniques, techniques that go beyond those utilized in the DataStage Essentials course. Accessing databases Connector stage overview - Use Connector stages to read from and write to relational tables - Working with the Connector stage properties Connector stage functionality - Before / After SQL - Sparse lookups - Optimize insert/update performance Error handling in Connector stages - Reject links - Reject conditions Multiple input links - Designing jobs using Connector stages with multiple input links - Ordering records across multiple input links File Connector stage - Read and write data to Hadoop file systems Demonstration 1: Handling database errors Demonstration 2: Parallel jobs with multiple Connector input links Demonstration 3: Using the File Connector stage to read and write HDFS files Processing unstructured data Using the Unstructured Data stage in DataStage jobs - Extract data from an Excel spreadsheet - Specify a data range for data extraction in an Unstructured Data stage - Specify document properties for data extraction. Demonstration 1: Processing unstructured data Data masking Using the Data Masking stage in DataStage jobs - Data masking techniques - Data masking policies - Applying policies for masquerading context-aware data types - Applying policies for masquerading generic data types - Repeatable replacement - Using reference tables - Creating custom reference tables Demonstration 1: Data masking Using data rules Introduction to data rules - Using the Data Rules Editor - Selecting data rules - Binding data rule variables - Output link constraints - Adding statistics and attributes to the output information Use the Data Rules stage to valid foreign key references in source data Create custom data rules Demonstration 1: Using data rules Processing XML data Introduction to the Hierarchical stage - Hierarchical stage Assembly editor - Use the Schema Library Manager to import and manage XML schemas Composing XML data - Using the HJoin step to create parent-child relationships between input lists - Using the Composer step Writing Hierarchical data to a relational table Using the Regroup step Consuming XML data - Using the XML Parser step - Propagating columns Topic 6: Transforming XML data - Using the Aggregate step - Using the Sort step - Using the Switch step - Using the H-Pivot step Demonstration 1: Importing XML schemas Demonstration 2: Compose hierarchical data Demonstration 3: Consume hierarchical data Demonstration 4: Transform hierarchical data Updating a star schema database Surrogate keys - Design a job that creates and updates a surrogate key source key file from a dimension table Slowly Changing Dimensions (SCD) stage - Star schema databases - SCD stage Fast Path pages - Specifying purpose codes - Dimension update specification - Design a job that processes a star schema database with Type 1 and Type 2 slowly changing dimensions Demonstration 1: Build a parallel job that updates a star schema database with two dimensions Additional course details: Nexus Humans KM423 IBM InfoSphere DataStage v11.5 - Advanced Data Processing 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 KM423 IBM InfoSphere DataStage v11.5 - Advanced Data Processing 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.

Discover the latest advancements and features in SQL 2021, the powerful database management system. Stay ahead with enhanced performance, security, and functionality for your data management needs.

Enhance your Excel skills with our comprehensive course covering 50 essential tips and techniques. Perfect for beginners and professionals alike, this course offers CPD accreditation and practical insights to boost your career prospects.

Level 1 Certificate in Understanding Data Protection and Data Security Unlock the world of Data Protection with our Level 1 Certificate course. Explore Data Protection Applications and delve into the essential Principles of GDPR. Learn about the Rights of Data Subjects, Data Protection Impact Assessments, Data Breaches, and the vital Exemptions in Data Protection. Learning Outcomes: Define Data Protection applications. Explain GDPR principles in Data Protection. Implement rights of a Data Subject. Evaluate Data Protection Impact Assessments (DPIA). Implement procedures for handling data breaches. Evaluate exemptions in Data Protection. More Benefits: LIFETIME access Device Compatibility Free Workplace Management Toolkit Level 1 Certificate in Understanding Data Protection and Data Security Course Syllabus Data Protection Applications: Explore the practical applications of data protection principles in various contexts, including business operations, information handling, and technology usage. Principles of GDPR: Gain a comprehensive understanding of the General Data Protection Regulation (GDPR) and its fundamental principles, including lawful processing, data subject rights, and accountability. Rights of Data Subject: Learn about the rights afforded to data subjects under data protection laws, such as the right to access, rectify, and erase personal data, and understand how to address these rights in compliance. Data Protection Impact Assessment (DPIA): Discover the importance of conducting DPIAs to assess and mitigate data protection risks associated with data processing activities, and learn how to perform effective DPIAs. Data Breaches: Understand the concept of data breaches, their implications, and the legal requirements for reporting and managing data breaches in accordance with data protection regulations. Exemptions in Data Protection: Explore specific exemptions and exceptions within data protection laws, including scenarios where data protection regulations may not apply or where limitations exist.