50 Data Quality courses

Exciting news! My popular 'Getting Started in Data Governance' course is making it's way across the pond! Due to numerous requests, I'm thrilled to announce that I will be hosting a U.S. edition of the course.

Duration 3 Days 18 CPD hours This course is intended for This course is aimed at anyone who wants to harness the power of data analytics in their organization including: Business Analysts, Data Analysts, Reporting and BI professionals Analytics professionals and Data Scientists who would like to learn Python Overview This course teaches delegates with no prior programming or data analytics experience how to perform data manipulation, data analysis and data visualization in Python. Mastery of these techniques and how to apply them to business problems will allow delegates to immediately add value in their workplace by extracting valuable insight from company data to allow better, data-driven decisions. Outcome: After attending this course, delegates will: Be able to write effective Python code Know how to access their data from a variety of sources using Python Know how to identify and fix data quality using Python Know how to manipulate data to create analysis ready data Know how to analyze and visualize data to drive data driven decisioning across your organization Becoming a world class data analytics practitioner requires mastery of the most sophisticated data analytics tools. These programming languages are some of the most powerful and flexible tools in the data analytics toolkit. From business questions to data analytics, and beyond For data analytics tasks to affect business decisions they must be driven by a business question. This section will formally outline how to move an analytics project through key phases of development from business question to business solution. Delegates will be able: to describe and understand the general analytics process. to describe and understand the different types of analytics can be used to derive data driven solutions to business to apply that knowledge to their business context Basic Python Programming Conventions This section will cover the basics of writing R programs. Topics covered will include: What is Python? Using Anaconda Writing Python programs Expressions and objects Functions and arguments Basic Python programming conventions Data Structures in Python This section will look at the basic data structures that Python uses and accessing data in Python. Topics covered will include: Vectors Arrays and matrices Factors Lists Data frames Loading .csv files into Python Connecting to External Data This section will look at loading data from other sources into Python. Topics covered will include: Loading .csv files into a pandas data frame Connecting to and loading data from a database into a panda data frame Data Manipulation in Python This section will look at how Python can be used to perform data manipulation operations to prepare datasets for analytics projects. Topics covered will include: Filtering data Deriving new fields Aggregating data Joining data sources Connecting to external data sources Descriptive Analytics and Basic Reporting in Python This section will explain how Python can be used to perform basic descriptive. Topics covered will include: Summary statistics Grouped summary statistics Using descriptive analytics to assess data quality Using descriptive analytics to created business report Using descriptive analytics to conduct exploratory analysis Statistical Analysis in Python This section will explain how Python can be used to created more interesting statistical analysis. Topics covered will include: Significance tests Correlation Linear regressions Using statistical output to create better business decisions. Data Visualisation in Python This section will explain how Python can be used to create effective charts and visualizations. Topics covered will include: Creating different chart types such as bar charts, box plots, histograms and line plots Formatting charts Best Practices Hints and Tips This section will go through some best practice considerations that should be adopted of you are applying Python in a business context.

Duration 4 Days 24 CPD hours This course is intended for This class is intended for experienced developers who are responsible for managing big data transformations including: Extracting, loading, transforming, cleaning, and validating data. Designing pipelines and architectures for data processing. Creating and maintaining machine learning and statistical models. Querying datasets, visualizing query results and creating reports Overview Design and build data processing systems on Google Cloud Platform. Leverage unstructured data using Spark and ML APIs on Cloud Dataproc. Process batch and streaming data by implementing autoscaling data pipelines on Cloud Dataflow. Derive business insights from extremely large datasets using Google BigQuery. Train, evaluate and predict using machine learning models using TensorFlow and Cloud ML. Enable instant insights from streaming data Get hands-on experience with designing and building data processing systems on Google Cloud. This course uses lectures, demos, and hand-on labs to show you how to design data processing systems, build end-to-end data pipelines, analyze data, and implement machine learning. This course covers structured, unstructured, and streaming data. Introduction to Data Engineering Explore the role of a data engineer. Analyze data engineering challenges. Intro to BigQuery. Data Lakes and Data Warehouses. Demo: Federated Queries with BigQuery. Transactional Databases vs Data Warehouses. Website Demo: Finding PII in your dataset with DLP API. Partner effectively with other data teams. Manage data access and governance. Build production-ready pipelines. Review GCP customer case study. Lab: Analyzing Data with BigQuery. Building a Data Lake Introduction to Data Lakes. Data Storage and ETL options on GCP. Building a Data Lake using Cloud Storage. Optional Demo: Optimizing cost with Google Cloud Storage classes and Cloud Functions. Securing Cloud Storage. Storing All Sorts of Data Types. Video Demo: Running federated queries on Parquet and ORC files in BigQuery. Cloud SQL as a relational Data Lake. Lab: Loading Taxi Data into Cloud SQL. Building a Data Warehouse The modern data warehouse. Intro to BigQuery. Demo: Query TB+ of data in seconds. Getting Started. Loading Data. Video Demo: Querying Cloud SQL from BigQuery. Lab: Loading Data into BigQuery. Exploring Schemas. Demo: Exploring BigQuery Public Datasets with SQL using INFORMATION_SCHEMA. Schema Design. Nested and Repeated Fields. Demo: Nested and repeated fields in BigQuery. Lab: Working with JSON and Array data in BigQuery. Optimizing with Partitioning and Clustering. Demo: Partitioned and Clustered Tables in BigQuery. Preview: Transforming Batch and Streaming Data. Introduction to Building Batch Data Pipelines EL, ELT, ETL. Quality considerations. How to carry out operations in BigQuery. Demo: ELT to improve data quality in BigQuery. Shortcomings. ETL to solve data quality issues. Executing Spark on Cloud Dataproc The Hadoop ecosystem. Running Hadoop on Cloud Dataproc. GCS instead of HDFS. Optimizing Dataproc. Lab: Running Apache Spark jobs on Cloud Dataproc. Serverless Data Processing with Cloud Dataflow Cloud Dataflow. Why customers value Dataflow. Dataflow Pipelines. Lab: A Simple Dataflow Pipeline (Python/Java). Lab: MapReduce in Dataflow (Python/Java). Lab: Side Inputs (Python/Java). Dataflow Templates. Dataflow SQL. Manage Data Pipelines with Cloud Data Fusion and Cloud Composer Building Batch Data Pipelines visually with Cloud Data Fusion. Components. UI Overview. Building a Pipeline. Exploring Data using Wrangler. Lab: Building and executing a pipeline graph in Cloud Data Fusion. Orchestrating work between GCP services with Cloud Composer. Apache Airflow Environment. DAGs and Operators. Workflow Scheduling. Optional Long Demo: Event-triggered Loading of data with Cloud Composer, Cloud Functions, Cloud Storage, and BigQuery. Monitoring and Logging. Lab: An Introduction to Cloud Composer. Introduction to Processing Streaming Data Processing Streaming Data. Serverless Messaging with Cloud Pub/Sub Cloud Pub/Sub. Lab: Publish Streaming Data into Pub/Sub. Cloud Dataflow Streaming Features Cloud Dataflow Streaming Features. Lab: Streaming Data Pipelines. High-Throughput BigQuery and Bigtable Streaming Features BigQuery Streaming Features. Lab: Streaming Analytics and Dashboards. Cloud Bigtable. Lab: Streaming Data Pipelines into Bigtable. Advanced BigQuery Functionality and Performance Analytic Window Functions. Using With Clauses. GIS Functions. Demo: Mapping Fastest Growing Zip Codes with BigQuery GeoViz. Performance Considerations. Lab: Optimizing your BigQuery Queries for Performance. Optional Lab: Creating Date-Partitioned Tables in BigQuery. Introduction to Analytics and AI What is AI?. From Ad-hoc Data Analysis to Data Driven Decisions. Options for ML models on GCP. Prebuilt ML model APIs for Unstructured Data Unstructured Data is Hard. ML APIs for Enriching Data. Lab: Using the Natural Language API to Classify Unstructured Text. Big Data Analytics with Cloud AI Platform Notebooks What's a Notebook. BigQuery Magic and Ties to Pandas. Lab: BigQuery in Jupyter Labs on AI Platform. Production ML Pipelines with Kubeflow Ways to do ML on GCP. Kubeflow. AI Hub. Lab: Running AI models on Kubeflow. Custom Model building with SQL in BigQuery ML BigQuery ML for Quick Model Building. Demo: Train a model with BigQuery ML to predict NYC taxi fares. Supported Models. Lab Option 1: Predict Bike Trip Duration with a Regression Model in BQML. Lab Option 2: Movie Recommendations in BigQuery ML. Custom Model building with Cloud AutoML Why Auto ML? Auto ML Vision. Auto ML NLP. Auto ML Tables.

Data is the lifeblood of any business, and data administrators are responsible for ensuring that it is accurate, secure, and accessible. With the rise of big data, the demand for skilled data administrators in the UK is skyrocketing, with an impressive growth rate of 15% in job demand over the past year alone. What's more, professionals in this domain command handsome salaries, ranging between £50,000 to £85,000 annually. If you're interested in a career in data administration, or if you're looking to advance your existing career, our Data Administration Processes course is the perfect place to start. This comprehensive course will teach you everything you need to know about data administration, from the basics of data modeling and database design to more advanced topics such as data security and disaster recovery. Embracing this course can be a pivotal stepping stone in solidifying your career as a top-tier data administrator. Why would you choose the Data Administration Processes course from Compliance Central: Lifetime access to Data Administration Processes course materials Full tutor support is available from Monday to Friday with the Data Administration Processes course Learn Data Administration Processes skills at your own pace from the comfort of your home Gain a complete understanding of Data Administration Processes course Accessible, informative Data Administration Processes learning modules designed by experts Get 24/7 help or advice from our email and live chat teams with the Data Administration Processes Study Data Administration Processes in your own time through your computer, tablet or mobile device A 100% learning satisfaction guarantee with your Data Administration Processes Course Data Administration Processes Curriculum Breakdown of the Data Administration Processes Course Module 01: Introduction Module 02: Agenda and Principles of Process Management Module 03: The Voice of the Process Module 04: Working as One Team for Improvement Module 05: Exercise: The Voice of the Customer Module 06: Tools for Data Analysis Module 07: The Pareto Chart Module 08: The Histogram Module 09: The Run Chart Module 10: Exercise: Presenting Performance Data Module 11: Understanding Variation Module 12: The Control Chart Module 13: Control Chart Example Module 14: Control Chart Special Cases Module 15: Interpreting the Control Chart Module 16: Control Chart Exercise Module 17: Strategies to Deal with Variation Module 18: Using Data to Drive Improvement Module 19: A Structure for Performance Measurement Module 20: Data Analysis Exercise Module 21: Course Project Module 22: Test your Understanding Data Administration Processes Course Learning Outcomes: Grasp foundational principles of data administration processes. Analyse and interpret various data visualisation tools. Understand and implement effective performance measurement structures. Recognize and address data variations strategically. Employ techniques to drive improvement through data. Present performance data with clarity and precision. Apply theoretical knowledge in real-world scenarios. CPD 10 CPD hours / points Accredited by CPD Quality Standards Who is this course for? The Data Administration Processes course helps aspiring professionals who want to obtain the knowledge and familiarise themselves with the skillsets to pursue a career in Data Administration Processes. It is also great for professionals who are already working in Data Administration Processes and want to get promoted at work. Requirements To enrol in this Data Administration Processes course, all you need is a basic understanding of the English Language and an internet connection. Career path The Data Administration Processes course will enhance your knowledge and improve your confidence. Data Analyst: £25,000 to £60,000 per year Data Entry Specialist: £18,000 to £30,000 per year Database Administrator: £30,000 to £65,000 per year Data Quality Manager: £35,000 to £70,000 per year Business Intelligence Analyst: £30,000 to £60,000 per year Certificates CPD Accredited PDF Certificate Digital certificate - Included CPD Accredited PDF Certificate CPD Accredited Hard Copy Certificate Hard copy certificate - £10.79 CPD Accredited Hard Copy Certificate Delivery Charge: Inside the UK: Free Outside of the UK: £9.99 each

Gain the solid skills and knowledge to kickstart a successful career and learn from the experts with this

Duration 4 Days 24 CPD hours This course is intended for This course is for consultants, project team members, and administrators who want to learn how to implement data provisioning and data transformation for their SAP HANA project. In this course, students will learn the essential techniques and tools of data provisioning and data transformation for SAP HANA. This course will help students identify the most effective data provisioning solutions for their SAP HANA project. Course Outline Trigger-based replication with SAP Landscape Transformation ETL based data provisioning using SAP Data Services Connecting SAP HANA to data sources using SAP HANA Smart Data Access Real-time data loading using Smart Data Streaming ETL based loading using Smart Data Integration and Smart Data Quality SAP HANA Direct Extractor Connection Fundamentals of SAP Replication Server Additional course details: Nexus Humans HA350 SAP HANA - Data Management 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 HA350 SAP HANA - Data Management 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 1 Days 6 CPD hours This course is intended for This class is designed for administrators preparing to take the Salesforce Marketing Cloud Administrator exam who are able to configure Marketing Cloud products using industry and product best practices. You should be generally familiar with data structure in subscriber data management. You should also be able to thoroughly navigate Setup, troubleshoot account configuration, and manage user requests. Overview When you complete this course, you will be able to: Recall exam objectives. Discuss product features and functionality covered on the exam. Assess your exam readiness by answering practice questions. Familiarize yourself with additional resources necessary to prepare for the exam. Take the next step in your career and become a Salesforce Certified Marketing Cloud Administrator. In this 1-day, expert-led certification prep class, boost your exam readiness with a detailed exam overview, exam resources, and practice exam questions to test your knowledge. This course includes a voucher to sit for the Salesforce Marketing Cloud Administrator exam. Course Outline Exam Overview Digital Marketing Proficiency Review Governance and Compliance in Relation to Digital Marketing Review Security Best Practices for Date, Permissions, and PII Review Marketing Cloud Product Inventory and Offerings Subscriber Data Management Review the Contact Model Review Data Quality Evaluation Review Preference and Profile Center Setup Review Business Units, Users, and Security Configuration Review Integrations Configuration Review Features in Setup Home Review Marketing Cloud Extension Products Channel Management Review Mobile Studio Configuration Review Email Studio Configuration Review Social Studio and Advertising Configuration Review Journey Builder Concepts and Use Cases Maintenance Review Data Extraction and Report Generation Solutions Review Monitoring and System Availability Review Additional Marketing Cloud Product Benefits Practice Exam and Wrap-up Complete a Practice Exam Review Next Steps

In today's competitive landscape, the imperative to enhance organisational performance has never been greater. At the heart of this quest lies the mastery of Quality Management Systems (QMS) and strategic training, essential for any entity aiming to outshine its competitors. Our 'Advanced Diploma in Quality Management and Strategic Training - ISO 9001 at QLS Level 7' course is meticulously crafted to arm participants with the knowledge and tools necessary to implement and manage an effective QMS. It intertwines the principles of Total Quality Management (TQM) with the nuances of managing a quality service, ensuring a holistic understanding that transcends traditional management practices. Through a deep dive into critical definitions, the course unfolds the fabric of quality management, elucidating the roles and responsibilities within a QMS. It adeptly covers the major changes in the field, incorporating the latest trends in financial data quality management and the strategic aspects of quality management systems. This course is not just about theory; it's an invitation to explore the practicalities of setting and achieving quality objectives, evaluating performance, and utilising helpful tools to ensure continuous improvement. Embarking on this journey, learners will uncover the qualities of a good manager and the strategic training necessary for excellence. The curriculum is designed to foster an environment where managing a quality service becomes second nature, preparing participants for a myriad of quality manager jobs. With a focus on the process approach and the context of the organisation, this course is a beacon for those seeking to elevate their career to new heights in quality management. Learning Outcomes: Understand the foundation and application of quality management systems and TQM principles within an organisation. Gain insights into effective strategies for managing a quality service and enhancing financial data quality management. Learn the essential qualities of a good manager and the role of strategic training in achieving organisational excellence. Master the process approach to QMS and how to set, achieve, and evaluate quality objectives effectively. Acquire the knowledge to navigate major changes in quality management and utilise helpful tools for continuous improvement. Why buy this Advanced Diploma in Quality Management and Strategic Training - ISO 9001 at QLS Level 7? Unlimited access to the course for a lifetime. Opportunity to earn a certificate accredited by the CPD Quality Standards and CIQ after completing this course. Structured lesson planning in line with industry standards. Immerse yourself in innovative and captivating course materials and activities. Assessments designed to evaluate advanced cognitive abilities and skill proficiency. Flexibility to complete the Course at your own pace, on your own schedule. Receive full tutor support throughout the week, from Monday to Friday, to enhance your learning experience. Unlock career resources for CV improvement, interview readiness, and job success. Who is this Advanced Diploma in Quality Management and Strategic Training - ISO 9001 at QLS Level 7 for? Individuals aspiring to pursue a career in quality management. Current managers seeking to enhance their strategic training and management skills. Professionals responsible for implementing and maintaining QMS in their organizatiorganisationsnterested in understanding the intricacies of ISO 9001 and its application. Learners aiming to acquire a comprehensive understanding of performance evaluation within QMS. Prerequisites This Advanced Diploma in Quality Management and Strategic Training - ISO 9001 at QLS Level 7 does not require you to have any prior qualifications or experience. You can just enrol and start learning.This Advanced Diploma in Quality Management and Strategic Training - ISO 9001 at QLS Level 7 was made by professionals and it is compatible with all PC's, Mac's, tablets and smartphones. You will be able to access the course from anywhere at any time as long as you have a good enough internet connection. Career path Quality Manager: £35,000 - £60,000 Per Annum QMS Specialist: £30,000 - £50,000 Per Annum Process Improvement Manager: £40,000 - £65,000 Per Annum Quality Assurance Director: £50,000 - £80,000 Per Annum Quality Systems Auditor: £25,000 - £45,000 Per Annum Strategic Quality Planner: £45,000 - £70,000 Per Annum Certification After studying the course materials of the Advanced Diploma in Quality Management and Strategic Training - ISO 9001 at QLS Level 7 there will be a written assignment test which you can take either during or at the end of the course. After successfully passing the test you will be able to claim the pdf certificate for £4.99. Original Hard Copy certificates need to be ordered at an additional cost of £8. Endorsed Certificate of Achievement from the Quality Licence Scheme Learners will be able to achieve an endorsed certificate after completing the course as proof of their achievement. You can order the endorsed certificate for only £135 to be delivered to your home by post. For international students, there is an additional postage charge of £10. Endorsement The Quality Licence Scheme (QLS) has endorsed this course for its high-quality, non-regulated provision and training programmes. The QLS is a UK-based organisation that sets standards for non-regulated training and learning. This endorsement means that the course has been reviewed and approved by the QLS and meets the highest quality standards. Please Note: Studyhub is a Compliance Central approved resale partner for Quality Licence Scheme Endorsed courses. Course Curriculum Course Structure Course Structure 00:07:00 Critical Definitions What is Quality 00:02:00 What is ISO 00:08:00 What is a System - Management System 00:02:00 What is Policy - Quality Policy 00:06:00 What is Vision, Mission & Strategy 00:03:00 QA Vs QC 00:06:00 Effectiveness Vs Efficiency 00:06:00 Verification Vs Validation 00:11:00 Conformity Vs Nonconformity Vs Defect 00:04:00 Correction Vs Corrective Action Vs Preventive Action 00:08:00 Risk & Preventive Action 00:06:00 What is Competence 00:03:00 What is the Context of the Organization 00:05:00 Who are the Interested parties 00:03:00 What are the Needs & expectations 00:05:00 Management System Requirements 00:01:00 Who is a customer 00:02:00 What is Customer Satisfaction 00:06:00 Product Vs Service Vs Process 00:05:00 Document Vs Record 00:06:00 What is Customer Complaint 00:02:00 Measuring Vs Monitoring Vs Performance 00:02:00 Who is Responsible Who is Responsible 00:12:00 Responsibility Vs Accountability 00:02:00 Quality Management Principles Quality Management Principles 00:17:00 Major Changes ISO 9001:2015 Core Concepts 00:08:00 Major terminology Differences 00:04:00 Documented Information 00:07:00 Major changes - Organizational Knowledge 00:05:00 Major changes - Risk Based Thinking 00:06:00 Process Approach Process Approach Concept-1 00:04:00 What is PDCA 00:05:00 Process Approach Concept-2 00:03:00 Process Approach in ISO 9001:2015 00:04:00 Key Benefits 00:07:00 PDCA in ISO 9001 2015 00:10:00 Context of the Organization Understanding the Organization and its Context 00:08:00 Internal & External issues 00:03:00 SWOT Analysis 00:06:00 Interested Parties & their Needs & Expectations 00:03:00 KANO Model 00:10:00 Understanding the context - Summary 00:08:00 Choosing your Strategic Objective 00:05:00 Strategic Map Examples-1 00:03:00 Strategic Planning Process 00:06:00 What is a Vision 00:06:00 How to Create a Vision Statement 00:08:00 What is a Mission 00:06:00 SMART GOAL 00:06:00 SMART Goal Example 00:04:00 Strategic Map Examples-2 00:10:00 Context Chapter Summary 00:07:00 Quality Objectives Quality Objectives & Planning 00:05:00 ISO & SMART 00:02:00 Objectives Origin 00:06:00 Objectives Examples 00:07:00 Goal Vs Objective-1 00:07:00 Goal Vs Objective Example 00:02:00 Goal Vs Objective-2 00:10:00 Performance Evaluation Performance Evaluation in ISO 9001:2015 00:10:00 Customer Satisfaction 00:06:00 Analysis & Evaluation 00:12:00 Key Performance Indicators 00:08:00 Dashboard Examples 00:07:00 Management Review Meetings 00:11:00 Improvement 00:16:00 Nonconformity & Corrective Action 00:06:00 Nonconformity & Corrective Action Example 00:06:00 Nonconformity & Corrective Action Origin 00:06:00 Continual Improvement 00:01:00 Analysis Mindset 00:09:00 Quantitative Vs Qualitative 00:16:00 Now What Now What? 00:11:00 Course Summary 00:10:00 Helpful Tools SIPOC 00:06:00 Flowcharts 00:04:00 Control Charts 00:04:00 Cause and Effect Diagram 00:06:00 Pareto Chart 00:07:00 5 WHYs 00:03:00 Other Tools 00:08:00 Finally! 00:01:00 See you soon Bonus Lecture 00:02:00 Assignment Assignment - Advanced Diploma in Quality Management and Strategic Training - ISO 9001 at QLS Level 7 04:00:00 Order your QLS Endorsed Certificate Order your QLS Endorsed Certificate 00:00:00

Duration 4 Days 24 CPD hours This course is intended for The workshop is designed for data scientists who currently use Python or R to work with smaller datasets on a single machine and who need to scale up their analyses and machine learning models to large datasets on distributed clusters. Data engineers and developers with some knowledge of data science and machine learning may also find this workshop useful. Overview Overview of data science and machine learning at scale Overview of the Hadoop ecosystem Working with HDFS data and Hive tables using Hue Introduction to Cloudera Data Science Workbench Overview of Apache Spark 2 Reading and writing data Inspecting data quality Cleansing and transforming data Summarizing and grouping data Combining, splitting, and reshaping data Exploring data Configuring, monitoring, and troubleshooting Spark applications Overview of machine learning in Spark MLlib Extracting, transforming, and selecting features Building and evaluating regression models Building and evaluating classification models Building and evaluating clustering models Cross-validating models and tuning hyperparameters Building machine learning pipelines Deploying machine learning models Spark, Spark SQL, and Spark MLlib PySpark and sparklyr Cloudera Data Science Workbench (CDSW) Hue This workshop covers data science and machine learning workflows at scale using Apache Spark 2 and other key components of the Hadoop ecosystem. The workshop emphasizes the use of data science and machine learning methods to address real-world business challenges. Using scenarios and datasets from a fictional technology company, students discover insights to support critical business decisions and develop data products to transform the business. The material is presented through a sequence of brief lectures, interactive demonstrations, extensive hands-on exercises, and discussions. The Apache Spark demonstrations and exercises are conducted in Python (with PySpark) and R (with sparklyr) using the Cloudera Data Science Workbench (CDSW) environment. The workshop is designed for data scientists who currently use Python or R to work with smaller datasets on a single machine and who need to scale up their analyses and machine learning models to large datasets on distributed clusters. Data engineers and developers with some knowledge of data science and machine learning may also find this workshop useful. Overview of data science and machine learning at scaleOverview of the Hadoop ecosystemWorking with HDFS data and Hive tables using HueIntroduction to Cloudera Data Science WorkbenchOverview of Apache Spark 2Reading and writing dataInspecting data qualityCleansing and transforming dataSummarizing and grouping dataCombining, splitting, and reshaping dataExploring dataConfiguring, monitoring, and troubleshooting Spark applicationsOverview of machine learning in Spark MLlibExtracting, transforming, and selecting featuresBuilding and evauating regression modelsBuilding and evaluating classification modelsBuilding and evaluating clustering modelsCross-validating models and tuning hyperparametersBuilding machine learning pipelinesDeploying machine learning models Additional course details: Nexus Humans Cloudera Data Scientist Training 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 Cloudera Data Scientist Training 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 The primary audience for this course are Application Consultants/Modelers and Project team members. Overview Get an overview of SAP HANA SPS09 and in-memory computing.Build an analytic data model with native HANA modeling tools.Understand the different approaches to provision data into SAP HANA.Learn how to connect to SAP HANA and consume HANA models. In this course, students get an overview of SAP HANA SPS09 and in-memory computing. Students will also gain an understanding of the different approaches to provision data into SAP HANA. Key concepts of SAP HANAWorking with SAP HANA StudioArchitecture of SAP in-memory computingModeling with SAP HANA Attribute Views Analytic Views Calculation Views Overview of data provisioning in SAP HANA with the tools Flat file upload SAP BusinessObjects Data Services SAP Landscape Transformation Replication Server SAP Replication Server SAP Direct Extractor Connection Smart Data Access Smart Data Integration / Smart Data Quality Smart Data Streaming SAP HANA Interfaces to BI client tools SAP BusinessObjects Analysis for Office SAP Design Studio SAP Lumira Additional course details: Nexus Humans HA100 SAP HANA - Introduction 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 HA100 SAP HANA - Introduction 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.