50 Data Warehouse courses delivered On Demand

Course Overview Learn about the functions of Microsoft Azure from this AZ-900 | Microsoft Azure Fundamentals Full Course course. The course will give you a clear understanding of the basics of Microsoft Azure and how you can use this cloud platform to grow and strengthen your online existence. In this AZ-900 | Microsoft Azure Fundamentals Full Course course, you will learn about the tools and basic functions of Microsoft Azure. You will be familiarized with the core Azure services, security, privacy and compliance policies. This course will teach you how you can secure your website and account using multi-factor authentication and protect data from hackers. This course will also help you to understand the supports Azure can offer you and get the best suitable one for you. Microsoft Azure is one of the most popular and safe cloud platforms. This AZ-900 | Microsoft Azure Fundamentals Full Course course will teach you the functions of Microsoft Azure from scratch. You don't need any prior knowledge or technical background to understand the lessons of this course. Learning Outcomes familiarize with the fundamentals of cloud services Understand the benefits of using cloud services Learn about the differences between capital expenditure and operational expenditure Be able to compare and contrast the IAAS, PAAS and SAAS service Learn about different cloud models and how they work Understand the core Azure architectural components Learn about the solutions you will get from Azure Learn about the management tools of Azure Get to know about the security and private privacy protocols of Microsoft Azure Understand how Azure identity services work Familiarize with role-based access control system Understand the policies and compliance standards in Azure Who is this course for? This comprehensive AZ-900 | Microsoft Azure Fundamentals Full Course is ideal for those who want to learn more about the functions of Microsoft Azure. You will learn about the application of Microsoft Azure and the career prospect from this course. Entry Requirement This course is available to all learners, of all academic backgrounds. Learners should be aged 16 or over to undertake the qualification. Good understanding of English language, numeracy and ICT are required to attend this course. Certification After you have successfully completed the course, you will be able to obtain an Accredited Certificate of Achievement. You can however also obtain a Course Completion Certificate following the course completion without sitting for the test. Certificates can be obtained either in hardcopy at the cost of £39 or in PDF format at the cost of £24. PDF certificate's turnaround time is 24 hours, and for the hardcopy certificate, it is 3-9 working days. Why choose us? Affordable, engaging & high-quality e-learning study materials; Tutorial videos/materials from the industry-leading experts; Study in a user-friendly, advanced online learning platform; Efficient exam systems for the assessment and instant result; The UK & internationally recognized accredited qualification; Access to course content on mobile, tablet or desktop from anywhere anytime; The benefit of career advancement opportunities; 24/7 student support via email. Career Path AZ-900 | Microsoft Azure Fundamentals Full Course is a useful qualification to possess and would be beneficial for any related profession or industry such as: Managers Managing Directors Management Executives Data Security Officers Programmers Microsoft Azure Developers Technicians Computer Operators Cloud Engineers Cloud Data Consultants Azure Consultants Data Scientists Course Introduction Introduction 00:04:00 Module 1 : Cloud Concepts What is Cloud Computing - I 00:05:00 What is Cloud Computing - II 00:06:00 Benefits of Cloud Computing 00:09:00 Key Concepts and Terminology 00:06:00 Economies of Scale 00:01:00 CapEx Vs OpEx 00:03:00 Cloud Models : What is Public Cloud 00:02:00 Cloud Models : Characteristics of Public Cloud 00:02:00 Cloud Models : What is Private Cloud 00:01:00 Cloud Models : Characteristics of Private Cloud 00:01:00 Cloud Models : Hybrid Cloud 00:01:00 Cloud Models : Characteristics of Hybrid Cloud 00:01:00 Review and What Next!! 00:01:00 What is IAAS 00:04:00 Use Cases of IAAS 00:02:00 What is PAAS ? 00:02:00 Use Cases of PAAS 00:04:00 What is SAAS ? 00:02:00 Cloud Models : Shared Responsibility Model 00:09:00 Module 2 : Core Azure Services Introduction 00:01:00 Azure Regions 00:01:00 Special Azure regions 00:01:00 Region pairs 00:01:00 Feature Availability Region Wise 00:01:00 Availability Zones 00:01:00 Availability Sets 00:02:00 What are Resource Groups? 00:02:00 Azure Resource Manager 00:01:00 What Next!! - Azure Core Services and Products 00:02:00 What is Azure Compute 00:01:00 Azure Virtual Machines - Audiocast Only 00:01:00 Azure Virtual Machines I - LAB 00:15:00 Azure Virtual Machines II - LAB 00:01:00 Azure Virtual Machines III - LAB 00:02:00 Azure Virtual Machines IV - LAB 00:04:00 Azure Virtual Machines V - LAB 00:03:00 Azure Virtual Machines VI - LAB 00:03:00 What are Containers? 00:04:00 Containers ( LAB Activity ) 00:07:00 Containers VS Virtual Machines 00:04:00 What Are Virtual Networks 00:01:00 Virtual Networks - LAB 00:15:00 Azure Load Balancer 00:01:00 VPN Gateway 00:01:00 Azure Application Gateway - I 00:02:00 Azure Application Gateway - II 00:01:00 Azure Content Delivery Networks (CDN's) 00:02:00 How CDN works ? 00:03:00 Azure CDN - Lab Activity 00:07:00 Azure Storage Services 00:01:00 Structured Data 00:01:00 Semi Structured Data 00:01:00 Unstructured Data 00:01:00 Azure Storage Account - Types 00:03:00 Azure Storage Account - Blob - Lab Activity - I 00:07:00 Azure Storage Account - Blog - Lab Activity - II 00:07:00 Azure Storage Account - Blob - Lab Activity - III 00:16:00 Azure Storage Account - Blog - Lab Activity - IV 00:09:00 Azure Storage Account - Blob - Lab Activity - V 00:04:00 Azure Storage Account - Blob - Lab Activity - VI 00:07:00 Azure Database Services 00:02:00 Azure SQL - Lab Demo 00:09:00 Azure MarketPlace 00:02:00 What is Internet of Things ( IOT ) - Intro 00:01:00 IOT Hub 00:01:00 IOT Hub Demo 00:09:00 Azure Big Data and Analytics 00:01:00 Azure SQL Data Warehouse 00:01:00 Azure HDInsights 00:01:00 Azure Data Lake Analytics 00:01:00 Machine Learning 00:02:00 Azure Machine Learning Services and Studio 00:02:00 What is Server less Computing ? 00:02:00 The concept of DevOps 00:03:00 Azure Management Tools 00:01:00 Creating Resources with Powershell - Lab Activity 00:05:00 Creating Resources with Azure CLI - Lab Activity 00:07:00 Provision Resources using Cloud Shell - Lab Activity 00:05:00 Deployment with JSON - Lab Activity 00:08:00 Azure Advisor 00:01:00 Module 2 : What did we learn 00:01:00 Module 3 Security, Privacy, Compliance and Trust What to expect in Module 3 00:01:00 Azure Firewalls 00:02:00 Azure Firewall - Lab Activity - notes 00:02:00 Azure Firewall - Lab Activity 00:19:00 Azure DDOS 00:02:00 Network Security Groups 00:03:00 Application Security Groups 00:02:00 Which Network Security Solution to choose from ? 00:04:00 AuthZ and AuthN 00:01:00 Azure Active Directory 00:02:00 Multi Factor Authentication 00:03:00 Azure Security Center 00:02:00 Azure Security center - LAB activity 00:08:00 Azure Key Vault 00:02:00 Azure Information Protection 00:02:00 Azure Advanced Threat Protection 00:04:00 What is Azure Policy 00:03:00 Azure Policy - Lab Activity 00:06:00 Azure Role Based Access Control ( RBAC ) 00:02:00 Azure Role Based Access Control ( RBAC ) - Lab Activity 00:07:00 Azure Locks 00:01:00 Azure Locks - Lab Activity 00:02:00 Azure Blueprints 00:01:00 Subscription Governance 00:02:00 Azure Tags 00:03:00 Azure Monitoring 00:02:00 Azure Monitor- Lab Activity 00:03:00 Azure Service Health 00:01:00 Monitoring Applications and Services 00:04:00 Compliance Terms and Requirements 00:02:00 Microsoft Privacy Statement 00:01:00 Microsoft Trust Center 00:01:00 Service Trust Portal 00:01:00 Azure Government Services 00:02:00 Azure Germany Services 00:01:00 Azure China 21Vianet 00:02:00 Module 4 : Azure Pricing and Support Module 4 Introduction : What tÌ¥o expect in this module 00:02:00 Azure Subscriptions 00:06:00 What are Management Groups 00:01:00 Purchase Azure Product & Services : Available Options 00:01:00 Usage Metrics 00:01:00 Factors Affecting Costs 00:02:00 The concept of Zones for Billing 00:02:00 Azure Pricing Calculator 00:04:00 Azure Total Cost of Ownership ( TCO ) 00:02:00 Ways to Minimize Costs in Azure 00:04:00 Azure Cost Management 00:02:00 Azure Support Plans 00:03:00 Alternative Support Options 00:02:00 Service Level Agreements ( SLA's ) 00:03:00 Composite SLA's 00:03:00 Improving Application SLA's 00:04:00 Public and Preview Features 00:01:00 Providing Feedback 00:01:00 General Availability 00:01:00 Azure Updates , Announcements and Roadmaps 00:01:00 Course Conclusion Course Conclusion 00:01:00 Certificate and Transcript Order Your Certificates and Transcripts 00:00:00

Warehouse management provides learners with the fundamental knowledge and skills needed to efficiently manage warehouse operations.

Discover Microsoft Fabric's architecture, master Data Engineering with OneLake and Spark, and elevate your skills in data warehousing and real-time processing. Compare SQL and KQL for better insights, and improve storytelling using Power BI. Finally, you will end with practical data science techniques and data management methods.

This course covers the important topics needed to pass the AWS Certified Data Analytics-Specialty exam (AWS DAS-C01). You will learn about Kinesis, EMR, DynamoDB, and Redshift, and get ready for the exam by working through quizzes, exercises, and practice exams, along with exploring essential tips and techniques.

Transport and Logistics Management with Warehouse Associate Training Diploma Master the intricacies of Transport and Logistics Management while acquiring the specialised skills of a Warehouse Associate. Take control of every link in the supply chain with our Transport and Logistics Management with Warehouse Associate Training Diploma. Learning Outcomes: Deliver exceptional customer service within logistics operations. Decode and apply business and international trade procedures pertinent to logistics. Optimise supply chain management to drive efficiency and effectiveness. Design warehouse layout configurations to maximise space and operational flow. Implement safety protocols and regulations within warehouse settings. Leverage cutting-edge technology for enhanced logistics and warehousing performance. More Benefits: LIFETIME access Device Compatibility Free Workplace Management Toolkit Key Modules from Transport and Logistics Management with Warehouse Associate Training Diploma: Customer Service and Logistics Perfect the art of balancing customer needs with operational requirements in logistics. Business and International Trade Procedures Adapt to the protocols of business and international trade to ensure seamless logistics operations. Supply Chain Management in Logistics Strategise and optimise supply chain processes to elevate logistics performance. Warehouse Layout Master layout planning to optimise warehouse operations, improving both space and efficiency. Warehouse Safety and Regulations Prioritise and enact safety measures to ensure a compliant and risk-free warehouse environment. Technology in Logistics and warehousing Adopt technological advancements to streamline operations, from inventory control to real-time tracking.

Prepare for the AWS Certified Solutions Architect - Associate (SAA-C03) exam. Learn about the AWS Management Console, S3 buckets, instances, database services, cloud security, costs associated with AWS, Amazon Elastic Compute Cloud (EC2), Amazon Virtual Private Cloud (VPC), Amazon Simple Storage Service (S3), and Amazon Elastic Block Store (EBS).

Getting Started The QUALIFI Level 3 Diploma in Data Science aims to offer learners a comprehensive introduction to data science. This Level 3 Diploma provides a modern and all-encompassing overview of data science, artificial intelligence, and machine learning. It covers the evolution of artificial intelligence and machine learning from their beginnings in the late 1950s to the emergence of the "big data" era in the early 2000s. It extends to the current AI and machine learning applications, including the associated challenges. In addition to covering standard machine learning models like linear and logistic regression, decision trees, and k-means clustering, this diploma introduces learners to two emerging areas of data science: synthetic data and graph data science. Moreover, the diploma familiarizes learners with the landscape of data analysis and the relevant analytical tools. It includes introducing Python programming so learners can effectively analyse, explore, and visualize data and implement fundamental data science models. Key Benefits Acquire the essential mathematical and statistical knowledge necessary for conducting fundamental data analysis. Cultivate analytical and machine learning proficiency using Python. Foster a solid grasp of data and its related processes, encompassing data cleaning, data structuring, and data preparation for analysis and visualisation. Gain insight into the expansive data science landscape and ecosystem, including relational databases, graph databases, programming languages like Python, visualisation tools, and various analytical instruments. Develop expertise in comprehending the machine learning procedures, including the ability to discern which algorithms are suited for distinct problems and to navigate the steps involved in constructing, testing, and validating a model. Attain an understanding of contemporary and emerging facets of data science and their applicability to modern challenges Key Highlights This course module prepares learners for higher-level Data science positions through personal and professional development. We will ensure your access to the first-class education needed to achieve your goals and dreams and to maximize future opportunities. Remember! The assessment for the Qualification is done based on assignments only, and you do not need to worry about writing any exam. With the School of Business and Technology London, you can complete the Qualification at your own pace, choosing online or blended learning from the comfort of your home. Learning and pathway materials and study guides developed by our qualified tutors will be available around the clock in our cutting-edge learning management system. Most importantly, at the School of Business and Technology London, we will provide comprehensive tutor support through our dedicated support desk. If you choose your course with blended learning, you will also enjoy live sessions with an assigned tutor, which you can book at your convenience. Career Pathways Upon completing the QUALIFI Level 3 Diploma in Data Science, learners can advance their studies or pursue employment opportunities. Data Analyst with an estimated average salary of £39,445 per annum Business Intelligence Analyst with an estimated average salary of £40,000 per annum Data entry specialist with an estimated average salary of £22,425 per annum Database Administrator with an estimated average salary of £44,185 per annum About Awarding Body QUALIFI, recognised by Ofqual awarding organisation has assembled a reputation for maintaining significant skills in a wide range of job roles and industries which comprises Leadership, Hospitality & Catering, Health and Social Care, Enterprise and Management, Process Outsourcing and Public Services. They are liable for awarding organisations and thereby ensuring quality assurance in Wales and Northern Ireland. What is included? Outstanding tutor support that gives you supportive guidance all through the course accomplishment through the SBTL Support Desk Portal. Access our cutting-edge learning management platform to access vital learning resources and communicate with the support desk team. Quality learning materials such as structured lecture notes, study guides, and practical applications, which include real-world examples and case studies, will enable you to apply your knowledge. Learning materials are provided in one of the three formats: PDF, PowerPoint, or Interactive Text Content on the learning portal. The tutors will provide Formative assessment feedback to improve the learners' achievements. Assessment materials are accessible through our online learning platform. Supervision for all modules. Multiplatform accessibility through an online learning platform facilitates SBTL in providing learners with course materials directly through smartphones, laptops, tablets or desktops, allowing students to study at their convenience. Live Classes (for Blended Learning Students only) Assessment Time-constrained scenario-based assignments No examinations Entry Requirements The qualification has been intentionally designed to ensure accessibility without imposing artificial barriers that limit entry. To enrol in this qualification, applicants must be 18 years of age or older. Admittance to the qualification will be managed through centre-led registration processes, which may involve interviews or other appropriate procedures. Despite the presence of advanced mathematics and statistics in higher-level data science courses, encompassing subjects such as linear algebra and differential calculus, this Level 3 Diploma only requires learners to be comfortable with mathematics at the GCSE level. The diploma's mathematical and statistical concepts are based on standard mathematical operations like addition, multiplication, and division. Before commencing the Level 3 Diploma in Data Science, learners are expected to meet the following minimum requirements: i) GCSE Mathematics with a grade of B or higher (equivalent to the new level 6 or above); and ii) GCSE English with a grade of C or higher (equivalent to the new level 4 or above). Furthermore, prior coding experience is not mandatory, although learners should be willing and comfortable with learning Python. Python has been selected for its user-friendly and easily learnable nature. In exceptional circumstances, applicants with substantial experience but lacking formal qualifications may be considered for admission, contingent upon completing an interview and demonstrating their ability to meet the demands of the capability. Progression Upon successful completion of the QUALIFI Level 3 Diploma in Data Science, learners will have several opportunities: Progress to QUALIFI Level 4 Diploma in Data Science: Graduates can advance their education and skills by enrolling in the QUALIFI Level 4 Diploma in Data Science, which offers a more advanced and comprehensive study of the field. Apply for Entry to a UK University for an Undergraduate Degree: This qualification opens doors to higher education, allowing learners to apply for entry to a UK university to pursue an undergraduate degree in a related field, such as data science, computer science, or a related discipline. Progress to Employment in an Associated Profession: Graduates of this program can enter the workforce and seek employment opportunities in professions related to data science, artificial intelligence, machine learning, data analysis, and other relevant fields. These progression options provide learners with a diverse range of opportunities for further education, career advancement, and professional development in the dynamic and rapidly evolving field of data science Why gain a QUALIFI Qualification? This suite of qualifications provides enormous opportunities to learners seeking career and professional development. The highlighting factor of this qualification is that: The learners attain career path support who wish to pursue their career in their denominated sectors; It helps provide a deep understanding of the health and social care sector and managing the organisations, which will, in turn, help enhance the learner's insight into their chosen sector. The qualification provides a real combination of disciplines and skills development opportunities. The Learners attain in-depth awareness concerning the organisation's functioning, aims and processes. They can also explore ways to respond positively to this challenging and complex health and social care environment. The learners will be introduced to managing the wide range of health and social care functions using theory, practice sessions and models that provide valuable knowledge. As a part of this suite of qualifications, the learners will be able to explore and attain hands-on training and experience in this field. Learners also acquire the ability to face and solve issues then and there by exposure to all the Units. The qualification will also help to Apply scientific and evaluative methods to develop those skills. Find out threats and opportunities. Develop knowledge in managerial, organisational and environmental issues. Develop and empower critical thinking and innovativeness to handle problems and difficulties. Practice judgement, own and take responsibility for decisions and actions. Develop the capacity to perceive and reflect on individual learning and improve their social and other transferable aptitudes and skills Learners must request before enrolment to interchange unit(s) other than the preselected units shown in the SBTL website because we need to make sure the availability of learning materials for the requested unit(s). SBTL will reject an application if the learning materials for the requested interchange unit(s) are unavailable. Learners are not allowed to make any request to interchange unit(s) once enrolment is complete. UNIT1- The Field of Data Science Reference No : H/650/4951 Credit : 6 || TQT : 60 This unit provides learners with an introduction to the field of data science, tracing its origins from the emergence of artificial intelligence and machine learning in the late 1950s, through the advent of the "big data" era in the early 2000s, to its contemporary applications in AI, machine learning, and deep learning, along with the associated challenges. UNIT2- Python for Data Science Reference No : J/650/4952 Credit : 9 || TQT : 90 This unit offers learners an introductory approach to Python programming tailored for data science. It begins by assuming no prior coding knowledge or familiarity with Python and proceeds to elucidate Python's fundamentals, including its design philosophy, syntax, naming conventions, and coding standards. UNIT3- Creating and Interpreting Visualisations in Data Science Reference No : K/650/4953 Credit : 3 || TQT : 30 This unit initiates learners into the realm of fundamental charts and visualisations, teaching them the art of creating and comprehending these graphical representations. It commences by elucidating the significance of visualisations in data comprehension and discerns the characteristics distinguishing effective visualisations from subpar ones. UNIT4- Data and Descriptive Statistics in Data Science Reference No : L/650/4954 Credit : 6 || TQT : 60 The primary objective of this unit is to acquaint learners with the foundational concepts of descriptive statistics and essential methods crucial for data analysis and data science. UNIT5- Fundamentals of Data Analytics Reference No : M/650/4955 Credit : 3 || TQT : 30 This unit will enable learners to distinguish between the roles of a Data Analyst, Data Scientist, and Data Engineer. Additionally, learners can provide an overview of the data ecosystem, encompassing databases and data warehouses, and gain familiarity with prominent vendors and diverse tools within this data ecosystem. UNIT6- Data Analysis with Python Reference No : R/650/4956 Credit : 3 || TQT : 30 This unit initiates learners into the fundamentals of data analysis using Python. It acquaints them with essential concepts like Pandas Data Frames and Series and the techniques of merging and joining data. UNIT7- Data Analysis with Python Reference No : R/650/4956 Credit : 3 || TQT : 30 This unit initiates learners into the fundamentals of data analysis using Python. It acquaints them with essential concepts like Pandas Data Frames and Series and the techniques of merging and joining data. UNIT8- Machine Learning Methods and Models in Data Science Reference No : T/650/4957 Credit : 3 || TQT : 30 This unit explores the practical applications of various methods in addressing real-world problems. It provides a summary of the key features of these different methods and highlights the challenges associated with each of them. UNIT9- The Machine Learning Process Reference No : Y/650/4958 Credit : 3 || TQT : 30 This unit provides an introduction to the numerous steps and procedures integral to the construction and assessment of machine learning models. UNIT10- Linear Regression in Data Science Reference No : A/650/4959 Credit : 3 || TQT : 30 This unit offers a foundational understanding of simple linear regression models, a crucial concept for predicting the value of one continuous variable based on another. Learners will gain the capability to estimate the best-fit line by computing regression parameters and comprehend the accuracy associated with this line of best-fit. UNIT11- Logistic Regression in Data Science Reference No : H/650/4960 Credit : 3 || TQT : 30 This unit introduces logistic regression, emphasizing its role as a classification algorithm. It delves into the fundamentals of binary logistic regression, covering essential concepts such as the logistic function, Odds ratio, and the Logit function. UNIT12- Decision Trees in Data Science Reference No : J/650/4961 Credit : 3 || TQT : 30 This unit offers an introductory exploration of decision trees' fundamental theory and practical application. It elucidates the process of constructing basic classification trees employing the standard ID3 decision-tree construction algorithm, including the node-splitting criteria based on information theory principles such as Entropy and Information Gain. Additionally, learners will gain hands-on experience in building and assessing decision tree models using Python. UNIT13- K-means clustering in Data Science Reference No : K/650/4962 Credit : 3 || TQT : 30 This unit initiates learners into unsupervised machine learning, focusing on the k-means clustering algorithm. It aims to give learners an intuitive understanding of the k-means clustering method and equip them with the skills to determine the optimal number of clusters. UNIT14- Synthetic Data for Privacy and Security in Data Science Reference No : L/650/4963 Credit : 6 || TQT : 60 This unit is designed to introduce learners to the emerging field of data science, specifically focusing on synthetic data and its applications in enhancing data privacy and security. UNIT15- Graphs and Graph Data Science Reference No : M/650/4964 Credit : 6 || TQT : 60 This unit offers a beginner-friendly introduction to graph theory, a foundational concept that underlies modern graph databases and graph analytics. Delivery Methods School of Business & Technology London provides various flexible delivery methods to its learners, including online learning and blended learning. Thus, learners can choose the mode of study as per their choice and convenience. The program is self-paced and accomplished through our cutting-edge Learning Management System. Learners can interact with tutors by messaging through the SBTL Support Desk Portal System to discuss the course materials, get guidance and assistance and request assessment feedbacks on assignments. We at SBTL offer outstanding support and infrastructure for both online and blended learning. We indeed pursue an innovative learning approach where traditional regular classroom-based learning is replaced by web-based learning and incredibly high support level. Learners enrolled at SBTL are allocated a dedicated tutor, whether online or blended learning, who provide learners with comprehensive guidance and support from start to finish. The significant difference between blended learning and online learning methods at SBTL is the Block Delivery of Online Live Sessions. Learners enrolled at SBTL on blended learning are offered a block delivery of online live sessions, which can be booked in advance on their convenience at additional cost. These live sessions are relevant to the learners' program of study and aim to enhance the student's comprehension of research, methodology and other essential study skills. We try to make these live sessions as communicating as possible by providing interactive activities and presentations. Resources and Support School of Business & Technology London is dedicated to offering excellent support on every step of your learning journey. School of Business & Technology London occupies a centralised tutor support desk portal. Our support team liaises with both tutors and learners to provide guidance, assessment feedback, and any other study support adequately and promptly. Once a learner raises a support request through the support desk portal (Be it for guidance, assessment feedback or any additional assistance), one of the support team members assign the relevant to request to an allocated tutor. As soon as the support receives a response from the allocated tutor, it will be made available to the learner in the portal. The support desk system is in place to assist the learners adequately and streamline all the support processes efficiently. Quality learning materials made by industry experts is a significant competitive edge of the School of Business & Technology London. Quality learning materials comprised of structured lecture notes, study guides, practical applications which includes real-world examples, and case studies that will enable you to apply your knowledge. Learning materials are provided in one of the three formats, such as PDF, PowerPoint, or Interactive Text Content on the learning portal. How does the Online Learning work at SBTL? We at SBTL follow a unique approach which differentiates us from other institutions. Indeed, we have taken distance education to a new phase where the support level is incredibly high.Now a days, convenience, flexibility and user-friendliness outweigh demands. Today, the transition from traditional classroom-based learning to online platforms is a significant result of these specifications. In this context, a crucial role played by online learning by leveraging the opportunities for convenience and easier access. It benefits the people who want to enhance their career, life and education in parallel streams. SBTL's simplified online learning facilitates an individual to progress towards the accomplishment of higher career growth without stress and dilemmas. How will you study online? With the School of Business & Technology London, you can study wherever you are. You finish your program with the utmost flexibility. You will be provided with comprehensive tutor support online through SBTL Support Desk portal. How will I get tutor support online? School of Business & Technology London occupies a centralised tutor support desk portal, through which our support team liaise with both tutors and learners to provide guidance, assessment feedback, and any other study support adequately and promptly. Once a learner raises a support request through the support desk portal (Be it for guidance, assessment feedback or any additional assistance), one of the support team members assign the relevant to request to an allocated tutor. As soon as the support receive a response from the allocated tutor, it will be made available to the learner in the portal. The support desk system is in place to assist the learners adequately and to streamline all the support process efficiently. Learners should expect to receive a response on queries like guidance and assistance within 1 - 2 working days. However, if the support request is for assessment feedback, learners will receive the reply with feedback as per the time frame outlined in the Assessment Feedback Policy.

Overview With the ever-increasing demand for Power BI in personal & professional settings, this online training aims at educating, nurturing, and upskilling individuals to stay ahead of the curve - whatever their level of expertise in Power BI may be. Learning about Power BI or keeping up to date on it can be confusing at times, and maybe even daunting! But that's not the case with this course from Compete High. We understand the different requirements coming with a wide variety of demographics looking to get skilled in Power BI . That's why we've developed this online training in a way that caters to learners with different goals in mind. The course materials are prepared with consultation from the experts of this field and all the information on Power BI is kept up to date on a regular basis so that learners don't get left behind on the current trends/updates. The self-paced online learning methodology by compete high in this Power BI course helps you learn whenever or however you wish, keeping in mind the busy schedule or possible inconveniences that come with physical classes. The easy-to-grasp, bite-sized lessons are proven to be most effective in memorising and learning the lessons by heart. On top of that, you have the opportunity to receive a certificate after successfully completing the course! Instead of searching for hours, enrol right away on this Power BI course from Compete High and accelerate your career in the right path with expert-outlined lessons and a guarantee of success in the long run. Who is this course for? While we refrain from discouraging anyone wanting to do this Power BI course or impose any sort of restrictions on doing this online training, people meeting any of the following criteria will benefit the most from it: Anyone looking for the basics of Power BI , Jobseekers in the relevant domains, Anyone with a ground knowledge/intermediate expertise in Power BI , Anyone looking for a certificate of completion on doing an online training on this topic, Students of Power BI , or anyone with an academic knowledge gap to bridge, Anyone with a general interest/curiosity Career Path This Power BI course smoothens the way up your career ladder with all the relevant information, skills, and online certificate of achievements. After successfully completing the course, you can expect to move one significant step closer to achieving your professional goals - whether it's securing that job you desire, getting the promotion you deserve, or setting up that business of your dreams. Course Curriculum Module 01 Introduction to Power BI Desktop Introduction to Power BI Desktop 00:00 Module 02 Discovering and Loading File-Based Data With PowerBI Desktop Discovering and Loading File-Based Data With PowerBI Desktop 00:00 Module 03 Loading Data From Databases and Data Warehouses Loading Data From Databases and Data Warehouses 00:00 Module 04 DirectQuery and Connect Live DirectQuery and Connect Live 00:00 Module 05 Loading Data from the Web and the Cloud Loading Data from the Web and the Cloud 00:00 Module 06 Dealing with Datasets Dealing with Datasets 00:00 Module 07 Data Transformation Data Transformation 00:00 Module 08 Data Mashup Data Mashup 00:00 Module 09 PowerBI.com PowerBI.com 00:00

The Warehouse Operative or warehouse management course equips individuals with fundamental competencies crucial for effective warehouse management.

Warehouse management provides learners with the fundamental knowledge and skills needed to efficiently manage warehouse operations.