Courses

Becoming an AWS Solutions Architect requires extensive knowledge of the entire AWS ecosystem, and an in-depth understanding of many storage, database, machine learning, and analytics services. In this course, AWS Certified Solutions Architect - Associate (SAA-C03): Storage, Databases, Machine Learning, and Big Data Analytics, you’ll learn to leverage many of these services within AWS. First, you’ll explore when to use the appropriate database technologies for your workloads. Next, you’ll discover how to leverage several of the machine learning and big data services for different scenarios. Finally, you’ll learn how to implement different services for migrations and analytics. When you’re finished with this course, you’ll have the skills and knowledge of AWS Solutions Architecture needed to pass exam objectives covering these different AWS services, as well as successfully implement them into real-world designs.

Explore the concept of a control plane for data in this 38-minute talk from Data Council. Learn about the reference architecture for the deconstructed data stack, including operational data stores, streaming systems, transformation engines, BI tools, warehouses, ML tools, and orchestrators. Dive into the fundamental characteristics of a control plane: breadth, latency, scale, source of truth, and auditability. Gain insights from Shirshanka Das, Co-founder and CEO of Acryl Data, as he shares his expertise in commercializing the open source DataHub project and his experience as the overall architect for Big Data at LinkedIn. Discover how a real-time metadata platform can benefit companies like LinkedIn, Stripe, Pinterest, Optum, and Expedia. Enhance your understanding of metadata and data management strategies in this informative presentation from a leading expert in the field.

Develop the expertise to architect modern data ecosystems. Learn advanced database design, data modeling, cloud integration, and governance to deliver secure, efficient, and scalable enterprise data solutions.

Explore the emerging field of big data science and its impact on the web in this 53-minute conference talk from PHP UK Conference 2012. Delve into the role of data scientists and learn how data mining techniques, including those using PHP, are being applied to create value from data itself. Discover how the future web is evolving to find answers, make discoveries, and connect disparate data sources to unlock collective wisdom. Gain insights from real-world data scientist case studies and examine hands-on text data mining code examples. Learn how big data touches all industries and aspects of life, and understand the challenges of comprehending and utilizing this vast amount of information to solve complex problems.

Explore the critical intersection of big data lakes and security vulnerabilities in this insightful conference talk from Security BSides London. Delve into the potential risks associated with large-scale data storage and management, examining how these vast repositories can become sources of significant data leaks if not properly secured. Learn about best practices for safeguarding big data lakes, understanding common attack vectors, and implementing robust security measures to protect sensitive information. Gain valuable insights from industry expert Ben Caller as he shares real-world examples and practical strategies for maintaining data integrity and confidentiality in the era of big data.

Big data is changing the way businesses operate. Driven by a new scale of data collection that provides massive levels of information, businesses are now able to analyse and gather data insights to make better-informed decisions. Data scientists and business analysts are in high-demand as companies look to use data to improve their business operations. In this Big Data MicroMasters program, you will learn tools and analytical methods to use data for decision-making, collect and organise data at scale, and gain an understanding of how data analysis can help to inform change within organisations. You’ll develop both the technical and computational skills that are in high demand across a range of industries. You’ll develop critical skills in programming for data science, computational thinking, algorithm design, big data fundamentals, and data-driven analysis, with plenty of opportunities to apply and explore your new learnings through a range of case studies.

Drive better business decisions with an overview of how big data is organized, analyzed, and interpreted. Apply your insights to real-world problems and questions. ********* Do you need to understand big data and how it will impact your business? This Specialization is for you. You will gain an understanding of what insights big data can provide through hands-on experience with the tools and systems used by big data scientists and engineers. Previous programming experience is not required! You will be guided through the basics of using Hadoop with MapReduce, Spark, Pig and Hive. By following along with provided code, you will experience how one can perform predictive modeling and leverage graph analytics to model problems. This specialization will prepare you to ask the right questions about data, communicate effectively with data scientists, and do basic exploration of large, complex datasets. In the final Capstone Project, developed in partnership with data software company Splunk, you’ll apply the skills you learned to do basic analyses of big data.

With Digital Data Consumption at its peak, the world has turned to Big Data for maintenance and analytics of this data. Private companies and research institutions capture terabytes of data about their users’ interactions, business, social media, and also sensors from devices such as mobile phones and automobiles. The challenge of this era is to make sense of this sea of data. For this reason, we have come up with this tutorial on "Big Data Analytics" The volume of data that one has to deal with has exploded to unimaginable levels in the past decade, and at the same time, the price of data storage has systematically reduced. Big Data Analytics largely involves collecting data from different sources, merge it in a way that it becomes available to be consumed by analysts, and finally deliver data products useful to the organization business. The process of converting large amounts of unstructured raw data, retrieved from different sources to a data product useful for organizations forms the core of Big Data Analytics. BigData is the latest buzzword in the IT Industry. Apache’s Hadoop is a leading Big Data platform used by IT giants Yahoo, Facebook & Google. In this tutorial, we have covered all the important topics such as, What is Big Data and Hadoop, What is Hive, What are their features and much more that will help you to get a hold over this concept.

Explore the intersection of big data and security in this thought-provoking conference talk from DerbyCon 3.0. Delve into the challenges and opportunities presented by the era of big data as Davi Ottenheimer shares insights on data management, privacy concerns, and the evolving landscape of information security. Gain valuable perspectives on how to navigate the complexities of big data while maintaining robust security practices in this 42-minute presentation.

This Big Data course will get you up & running with the definitions and technologies you need to know and the vendors you need to know about. Sign up today! Big Data technology is now critical to and pervasive in the enterprise. In this course, Big Data: The Big Picture, you’ll learn about the concepts, core technologies and competitive landscape in the Big Data arena. First, you’ll explore key Big Data terms, technologies and professional roles. Next, you’ll discover who the key vendors are in the Big Data space. Finally, you’ll learn strategic approaches to Big Data adoption. When you’re finished with this course, you’ll have the technology context and market understanding needed to plan a Big Data technology implementation for your team, business unit organization.

Get your Salesforce Data Architect certification with this course, aligned with the Spring 23 exam guide objectives What you'll learn: Data modeling/Database DesignCustom fields, master detail, lookup relationshipsMaking best use of Salesforce standard and big objectsSalesforce metadataMaster Data ManagementSalesforce license typesData consistency techniques in SalesforceSalesforce Consent Management ObjectsData Governance TechniquesLarge Data Volume considerationsIndexing, LDV migrations, performanceData Virtualization in SalesforceSalesforce Platform declarative and programming conceptsData Quality Skills (concerned with clean data) The Salesforce Certified Data Architect credential is intended for the architect who assesses the architecture environment and requirements; and designs sound, scalable, and performant solutions on the Salesforce platform.This certification is part of the Application Architect certification, and it emphasizes on the data side of Salesforce. I highly encourage you to take this course even if you are not seeking to get your Application Architecture certification as it contains key objectives related to data in Salesforce.The Salesforce Certified Data Architect Course was designed to be fully aligned with the official Salesforce Data Architect certification exam guide objectives. Ialways like to organize my Salesforce study for any certification to be based on the objectives. I always get the latest exam guide, understand each objective, and go through every requirement of every objective, this way I am sure to cover everything needed to pass the exam.The sections of this course are aligned with the objectives, and they are:Data modeling/Database DesignMaster Data ManagementSalesforce Data ManagementData GovernanceLarge Data Volume considerationsData MigrationAll supporting references are also included. These include Trailhead modules and trails, external links for articles and videos.I will make sure to update the videos after every release, if Salesforce changes the exam objectives.Finally, I have been there, I spent hours and hours preparing for this exam, I dissected each and every topic of the Study Guide, and took tons of notes, just like I did when preparing for my other certifications. I guarantee that after completing this course, after exploring all the provided resources, and after practicing on the Salesforce environment, you will pass this exam, and you will become a Salesforce Certified Data Architect! Good Luck! Walid

The Qlik Sense Developer Bootcamp What you'll learn: Create a data model in QlikSenseCreate and maintain data connectionsDevelop and debug QlikSense scriptCleanse and transform source dataResolve data model issuesOptimization for performanceCreate and use Qlik Data Files (QVD) filesManage security with Section Access Welcome to QlikSese Data Architect Masterclass. In this course, you will master skill to develop associativedata models in Qlik Sense from scratch.In this brand new QlikSense masterclass, you will learn step-by-step to cleanse, transform, and unify data from multiple disparate sources using June 2018 release version and its features.You will build optimized associative data model using powerful ETL scripting and learn how to deal withcomplex data integration challenges.Throughout the course, with hands-on examples and challenges, you will master QlikSense developer skill to build a data model which business analysts can use to build insight driven, self service applications for your enterprise.QlikSense data architect masterclass topics include: data connections, cleansing and transforming source data, resolvingdata model issues, optimization for performance, using QlikView Data Files (QVD) files and data model security.This course is designed so that anyone can learn how to develop data models in Qlik Sense!

Gain practical, real-world experience in data architecture through this hands-on capstone project course, developing skills highly valued by employers. During this course, you’ll apply all that you’ve learned throughout the Data Architecture Professional Certificate. As you work through the course, you’ll evaluate, design, migrate, and integrate enterprise data systems through a case study. In the capstone project, you will assess the current data architectures of two organizations, highlighting their strengths and identifying areas for improvement. Based on this analysis, you will design and implement a unified and efficient architecture for the newly merged entity, aligning with business goals. The project includes working with both RDBMS and NoSQL databases and developing ETL pipelines to ensure smooth data integration and flow. Additionally, you will create a data governance plan that addresses regulatory compliance and outlines strategies for data protection. Overall, this real-world inspired scenario will give you plenty to talk about implementing an architecture and managing a system transition in interviews. If you’re keen to add practical experience to your portfolio that employers look for, enroll today!

Dive into the world of Big Data with this comprehensive 2.5-hour tutorial series. Learn the fundamentals of Big Data, set up a Hadoop system, master essential Linux commands, and explore Hadoop architecture. Gain practical knowledge on scaling, HDFS design, and Hadoop 2.X Yarn architecture. Progress through 13 tutorials covering topics from basic introductions to advanced concepts, preparing you for real-world Big Data challenges.

COURSE OUTLINE : In today's fast-paced digital world , the incredible amount of data being generated every minute has grown tremendously from sensors used to gather climate information, posts to social media sites, digital pictures and videos, purchase transaction records, and GPS signals from cell phone to name a few. This amount of large data with different velocities and varieties is termed as big data and its analytics enables professionals to convert extensive data through statistical and quantitative analysis into powerful insights that can drive efficient decisions. This course provides an in-depth understanding of terminologies and the core concepts behind big data problems, applications, systems and the techniques, that underlie todays big data computing technologies. It provides an introduction to some of the most common frameworks such as Apache Spark, Hadoop, MapReduce, Large scale data storage technologies such as in-memory key/value storage systems, NoSQL distributed databases, Apache Cassandra, HBase and Big Data Streaming Platforms such as Apache Spark Streaming, Apache Kafka Streams that has made big data analysis easier and more accessible. And while discussing the concepts and techniques, we will also look at various applications of Big Data Analytics using Machine Learning, Deep Learning, Graph Processing and many others. The course is suitable for all UG/PG students and practicing engineers/ scientists from the diverse fields and interested in learning about the novel cutting-edge techniques and applications of Big Data Computing.

Dive into a comprehensive 19-hour course on Big Data Analytics offered by the California Institute of Technology. Explore best programming practices, data models, relational databases, SQL, and alternative databases. Learn about inference, uncertainty, and probability basics. Master the R programming language for data analysis. Delve into machine learning concepts, including supervised and unsupervised learning, classification, and clustering techniques. Study decision trees, random forests, and their applications in space exploration and cancer research. Examine pattern recognition, dimensionality reduction, and feature selection methods. Discover data visualization principles, tools, and techniques for effective communication. Investigate cloud computing, algorithmic approaches to big data, semantics, and genetic algorithms. Conclude with an in-depth look at big data architecture fundamentals and content detection and analysis for large-scale datasets.

Explore a real-world business case study on big data analytics in this 22-minute conference talk from GOTO Stockholm 2017. Delve into the power of graph technology and fast big data ingestion for solving complex problems like anti-money laundering and fraud detection. Learn how legacy systems, data management challenges, and the evolution of big data impact modern business solutions. Discover the potential of deep learning and innovative approaches like NeoConnections in tackling fraud and AML issues. Gain insights from Paul Smith, Data Science Director at Trifork, as he shares his experience and expertise in leveraging advanced analytics for practical business applications.

Big data is a fast-growing field and skills in the area are some of the most in demand today. The Big Data Analytics program from Queensland University of Technology (QUT) comprises four online courses that each look at a different element of big data. You’ll begin by examining how big data is collected and stored, before going on to explore how statistical inference, machine learning, mathematical modelling and data visualisation are used in its analysis. You’ll become familiar with predictive analysis, dimension reduction, machine learning, clustering techniques and decision trees, before going on to look at the maths that underpins many of the tools you can use to manage and analyse big data. Accessible for free on desktop, tablet or mobile and delivered in bite-sized chunks, the courses provide a flexible way to develop your big data analytics skills. When you complete all four courses, upgrade and earn a Certificate of Achievement for each, you will receive a FutureLearn Award as proof of completing the program of study.

Big Data Essentials is a comprehensive introduction to the world of big data. Starting with the definition of big data, we describe the various characteristics of big data and its sources. Using real world examples, we highlight the growing importance of big data. We discuss architectural requirements, principles of big data infrastructures, and the intersection of cloud computing with big data. We also provide an overview of the most popular big data technologies including core Hadoop, the Hadoop ecosystem (Hive, Pig, Sqoop, Flume, Kafka, Storm, Ambari, Oozie, Zookeeper), NoSQL databases, and Apache Spark. We conclude this lesson with a tour of the different types of analytics that can be performed on big data as well as the various techniques and tools used.

If you’re completely new to big data and aren’t quite sure what it is, why it’s necessary, and how it works, then this is the course for you! We are going to clarify what big data is (and isn’t), while also defining some other related terms around data characterization and analysis methods. Then, we talk about some architectural problems with big data and how we solve them with cluster computing, distributed storage, and cluster management. Lastly, we will cover some of the popular technologies and illustrate how big data is used in the real world to hopefully shine a light on how big data is already impacting your daily life — whether you realize it or not. Let’s get started!