The top 20 Master Data courses you need to take

1. Master Data in SAP

4.3

(67)

A warm welcome to the Master Data in SAP course by Uplatz. Master Data is the data that is created centrally and is consistent & valid for all applications. It remains constant over time but it is to be updated on a regular basis. For e. g., Vendor is a type of master data that is used for creating purchase orders or contracts. Master data in SAP is used as a base for any transaction. If you are producing, transferring stock, selling, purchasing, doing physical inventory, whatever your activity may be, it requires certain master data to be maintained. SAP Master Data is of the following types −1) Material Master Data2) Customer Master Data3) Vendor Master Data4) Pricing/conditions Master Data5) Warehouse management Master Data (storage bin master data)Material master records contain the information of materials that an organization purchases, manufactures, or sells. Vendor master record contains the information about vendors - address, financial data, payment terms, purchasing data such as currency, order value. Purchase info record consists of detailed information about materials and vendors supplying the required materials. Source list is a type of master data that determines the preferred sources of supply for a material. In SAP, material master data refer to all the material master records, which are stored in SAP system. The material master is the central source of information for a material related to several application area (Purchasing, storage, accounting, sales, etc) based on material type. In SAP MM, material master data is maintained at plant level and accounting information is maintained at valuation area level. The valuation are at organization level at which material are valuated. The valuation are can be be a plant or a company code. Master data in SAP is the core data of an enterprise that exists independently of specific business transactions and is referenced in business transactions. It builds the foundation for the smooth execution of business processes and well-informed business decisions. With reference to material management module, the business users in purchase department maintains the following material master data: Material master recordsVendor master recordsPurchase info recordsSource list recordsQuota arrangement recordsService master recordBatch master recordCondition record, etc. There are important configuration steps in Material Master like defining Material Types, Number ranges, Field selection, Quantity and value update, etc...

2. Mastering Data Modeling Fundamentals

4.4

(8,504)

If you are a current or aspiring IT professional in search of sound, practical techniques to analyze and model data as part of the overall data management lifecycle, this is the course for you. During the course, you'll put what you learn to work and define sample data model segments in both "classic" entity-relationship notation and also the "crow's foot" notation to help emphasize the best practices and techniques covered in this course. Each section has either scenario based quiz questions or hands on assignments that emphasizes key learning objectives for that section's material. This way, you can be confident as you move through the course that you're picking up the key points about data modeling. To build this course, I drew from more than 30 years of my own work involving data modeling and related disciplines. Long ago, in the late 1980s, I was a software engineer at what was then the world's second largest computer systems vendor, Digital Equipment Corporation. I wrote software for a "conceptual and logical database design tool" - in other words, a data modeling tool. My own consulting firm, Thinking Helmet, Inc., specializes in data management and analytics-focused disciplines for which data modeling is essential. I've rolled up my sleeves and personally tackled every aspect of what you'll learn in this course. I've even learned a few painful lessons, and have built a healthy share of "lessons learned" into the course material. In this course, I take you from the fundamentals and concepts of data modeling all the way through a number of best practices and techniques that you'll need to build data models in your organization. You'll find many examples that clearly demonstrate the key concepts and techniques covered throughout the course. By the end of the course, you'll be all set to not only put these principles to work, but also to make the key data modeling and design decisions required by the "art" of data modeling that transcend the nuts-and-bolts techniques and design patterns. Specifically, this course will cover: Foundational data modeling concepts and fundamentalsThe symbiotic relationship between data modeling and database design (Hint: the two are not exactly the same!)Different modeling approaches, techniques, and notations that you can put to workThe fundamentals of entities, attributes, and relationships, as well as how to express these concepts in multiple modeling notationsHow we incorporate real-world complexities into our entities, attributes, and relationshipsThe data modeling lifecycle that includes forward engineering a conceptual data model to a logical and then a physical model, as well as how we reverse-engineer a physical data model back to the conceptual levelDifferent software-based approaches for data modeling toolsData modeling is both an art and a science. While we have developed a large body of best practices over the years, we still have to make this-or-that types of decisions throughout our data modeling work, often based on deep experience rather than specific rules. That's what I've instilled into this course: the fusion of data modeling art and science that you can bring to your organization and your own work. So come join me on this journey through the world of data modeling!...

3. Master Data Engineering using Azure Data Analytics

4.5

(113)

Data Engineering is all about building Data Pipelines to get data from multiple sources into Data Lakes or Data Warehouses and then from Data Lakes or Data Warehouses to downstream systems. As part of this course, I will walk you through how to build Data Engineering Pipelines using Azure Data Analytics Stack. It includes services such as Azure Storage (both Blob and ADLS), ADF Data Flow, ADF Pipeline, Azure SQL, Azure Synapse, Azure Databricks, and many more. As part of this course, first, you will go ahead and set up the environment to learn using VS Code on Windows and Mac. Once the environment is ready, you need to sign up for Azure Portal. We will provide all the instructions to sign up for Azure Portal Account including reviewing billing as well as getting USD 200 Credit valid for up to a month. We typically use Azure Storage as Data Lake. As part of this course, you will learn how to use Azure Storage as Data Lake along with how to manage the files in Azure Storage using tools such as Azure Storage Explorer. ADF (Azure Data Factory) is used for both ETL as well as Orchestration. First, you will understand how to perform ETL using ADF Data Flow. The source and target will be Files in Azure Storage Account. As part of this process, you will also learn how to set up Linked Services and Data Sets in ADF (Azure Data Factory). Once ADF Data Flow is ready, you will go ahead and build Pipeline for Orchestration using ADF Pipeline. You will also learn how to parameterize and also how to take care of baseline load. You will also understand key performance tuning techniques using ADF Pipeline such as controlling the number of partitions, custom integration runtimes (IR), etc. Azure provides RDBMS as different services for Postgres, SQL Server, etc. You will learn how to set up Azure SQL Once the Azure SQL is set up, you will also understand how to create required tables and run queries against them. ADF provides ADF Data Copy to copy data from different sources and different targets. Once the Database tables are ready you will use ADF Data Copy to copy data into the tables. Azure provides Synapse Analytics for Data Warehouse. You will get an overview of both serverless as well as dedicated pools. You will end up setting up Dedicated Pool for ETL using ADF. Once Azure SQL and Azure Synapse are ready, you will build ETL Pipeline using ADF Data Flow and Orchestrate using ADF Pipeline. Azure Databricks is the service for Big Data Processing using Spark Engine. You will learn how to set up Azure Databricks, integrate with ADLS, and also managing secrets. You will also get an overview of Spark SQL and Pyspark Data Frame APIs using Azure Databricks. You will also build ELT Pipeline using Databricks Jobs and Workflows where tasks are defined based on Pyspark as well as Spark SQL. You will also understand how to build ADF Pipelines to orchestrate Databricks Notebooks...

4. Master Data Engineering using GCP Data Analytics

4.5

(318)

Data Engineering is all about building Data Pipelines to get data from multiple sources into Data Lakes or Data Warehouses and then from Data Lakes or Data Warehouses to downstream systems. As part of this course, I will walk you through how to build Data Engineering Pipelines using GCP Data Analytics Stack. It includes services such as Google Cloud Storage, Google BigQuery, GCP Dataproc, Databricks on GCP, and many more. As part of this course, first you will go ahead and setup environment to learn using VS Code on Windows and Mac. Once the environment is ready, you need to sign up for Google Cloud Account. We will provide all the instructions to sign up for Google Cloud Account including reviewing billing as well as getting USD 300 Credit. We typically use Cloud Object Storage as Data Lake. As part of this course, you will learn how to use Google Cloud Storage as Data Lake along with how to manage the files in Google Cloud Storage both by using commands as well as Python. It also covers, integration of Pandas with files in Google Cloud Storage. GCP provides RDBMS as service via Cloud SQL. You will learn how to setup Postgresql Database Server using Cloud SQL. Once the Database Server is setup, you will also take care of setting up required application database and user. You will also understand how to develop Python based applications by integrating with GCP Secretmanager to retrieve the credentials. One of the key usage of Data is nothing but building reports and dashboards. Typically reports and dashboards are built using reporting tools pointing to Data Warehouse. As part of Google Data Analytics Services, BigQuery can be used as Data Warehouse. You will learn the features of BigQuery as a Data Warehouse along with key integrations using Python and Pandas. At times, we need to process heavy volumes of data which also known as Big Data Processing. GCP Dataproc is a fully manage Big Data Service with Hadoop, Spark, Kafka, etc. You will not only learn how to setup the GCP Dataproc cluster, but also you will learn how to use single node Dataproc cluster for the development. You will setup development environment using VS Code with remote connection to the Dataproc Cluster. Once you understand how to get started with Big Data Processing using Dataproc, you will take care of building end to end ELT Data Pipelines using Dataproc Workflow Templates. You will learn all key commands to submit Dataproc Jobs as well as Workflows. You will end up building ELT Pipelines using Spark SQL. While Dataproc is GCP Native Big Data Service, Databricks is another prominent Big Data Service available in GCP. You will also understand how to get started with Databricks on GCP. Once you go through the details about how to get started with Databricks on GCP, you will take care of building end to end ELT Datapipelins using Databricks Jobs and Workflows. Towards the end of the course you should be fairly comfortable with BigQuery for Data Warehouse and GCP Dataproc for Data Processing, you will learn how to integrate these two key services by building end to end ELT Data Pipeline using Dataproc Workflow. You will also understand how to include Pyspark based application with Spark BigQuery connector as part of the Pipeline. In the process of building Data Pipelines, you will also revise application development life cycle of Spark, troubleshooting issues related to the spark using relevant web interfaces such as YARN Timeline Server, Spark UI, etc...

5. Master Data Mining in Data Science & Machine Learning

4

(133)

If you are looking to build strong foundations and understand advanced Data Mining techniques using Industry-standard Machine Learning models and algorithms then this is the perfect course is for you. We have covered everything you need about Data Mining and its processes, Machine Learning Models, and how to implement them in the real world. Data mining means mining the data. It is defined as finding hidden insights(information) from the database and extract patterns from the data. Data mining is an automated process that consists of searching large datasets for patterns humans might not spot. In this course, you will get advanced knowledge on Data Mining. This course begins by providing you the complete knowledge about the introduction of Data Mining. This course is a complete package for everyone wanting to pursue a career in data mining. In this course, you will cover the following topics:-Data Mining Standard Processes. KDD- Knowledge Discovery in Databases. Introduction to SEMMA. Introduction to CRISP- DM. Introduction to TDSP- Team Data Science Process. Survival Analysis. Introduction to Survival Analysis. Kaplan Meyer Estimator introduction. Log Rank Test introduction. Cox Hazards Regression. Clustering Analysis. KMeans clustering. Gaussian Mixture Model. Dimensionality reduction. Introduction to Data Reduction. PCA - Principal Component Analysis. T-SNE. LDA - Linear Discriminant Analysis. Association Rule Learning. Transaction List. Encoding Transactions. Aprior Algorithm and Visualization. Tree based models. Decision Trees. Attribute selection method- Gini Index and Entropy. Concept of Bagging. Random Forest. Boosting Algorithm. Introduction to Adaboost and Gradient Boosting. Introduction to XGBoost. Model Explanationability. Introduction to SHAP. Local and Global Interpretability. Introduction to LIME. This course is a complete package. Lots and lots of quizzes and exercises are waiting for you. You will also have access to all the resources used in this course. Instructor Support - Quick Instructor Support for any queries. I'm looking forward to see you in the course! Enroll now and become an expert in Data Mining...

6. Mastering Data Visualization with Python

4.7

(167)

This course will help you draw meaningful knowledge from the data you have. Three systems of data visualization in R are covered in this course: A. Pandas    B. Matplotlib  C. Seaborn       A. Types of graphs covered in the course using the pandas package: Time-series: Line PlotSingle Discrete Variable: Bar Plot, Pie PlotSingle Continuous Variable:  Histogram, Density or KDE Plot, Box-Whisker Plot Two Continuous Variable: Scatter PlotTwo Variable: One Continuous, One Discrete: Box-Whisker PlotB. Types of graphs using Matplotlib library: Time-series: Line PlotSingle Discrete Variable: Bar Plot, Pie PlotSingle Continuous Variable:  Histogram, Density or KDE Plot, Box-Whisker Plot Two Continuous Variable: Scatter PlotIn addition, we will cover subplots as well, where multiple axes can be plotted on a single figure. C. Types of graphs using Seaborn library: In this we will cover three broad categories of plots: relplot (Relational Plots): Scatter Plot and Line Plotdisplot (Distribution Plots): Histogram, KDE, ECDF and Rug Plotscatplot (Categorical Plots): Strip Plot, Swarm Plot, Box Plot, Violin Plot, Point Plot and Bar plotIn addition to these three categories, we will cover these three special kinds of plots: Joint Plot, Pair Plot and Linear Model PlotIn the end, we will discuss the customization of plots by creating themes based on the style, context, colour palette and font...

7. Mastering Data Visualization with R

4.6

(477)

This course will help you draw meaningful knowledge from the data you have. Three systems of data visualization in R are covered in this course: A. Base Graphics    B. Lattice package  C. GGPlot2       A. Types of graphs covered in the course using the base R package: Single Continuous Variable:  Histogram, Density Plot, Box-Whisker Plot Single Discrete Variable: Bar Chart Two Continuous Variable: Scatter PlotTwo Variable: One Continuous, One Discrete: Box-Whisker Plot, Pie Chart, Dot Chart, Strip Chart Two Variables: Both Discrete: Mosaic Plot, Stacked Bar Plot       Time series: Line ChartsB. Types of graphs covered in the Lattice package: Histogram, Density Plot, Box-Whisker Plot, Bar Chart, Scatter Plot, Dot Chart, Strip ChartC. Graphs covered in GGPlot2 package: In this section you will learn about 7 layers in ggplot() and how to use these. In addition there is a project of selecting a diamond from the dataset  of 54000 diamonds, based on my budget. Commonly Used Graphs: Histogram, Density Plot, Box-Whisker Plot, Bar Chart, Scatter Plot, Dot Chart, Strip ChartWhat are other students saying about this course?Very thorough. Covers all the details without glossing over anything. Good consistent pace and nice short segments. Very diligent in always saying what keys he was pressing during the demos, which is often overlooked. Excellent course. (5 stars by Roger Holeywell)Explanations are clear and coherent. This course is well structured and very-very useful. Thank you so much for your help! (5 stars by Martina Katalin Szabó)Todos os cursos oferecidos pelo Prof. Sandeep Kumar na Udemy são excelentes, especialmente em análise e visualização de dados.(5 stars by Jose Maria Nogueira da Costa )...

8. Mastering Data Analysis in Excel

4.4

(456)

5 hours of professional course for everyone who wants to learn essentials of data analysis and visualization in Excel and become an Advanced Excel User. Join to over 5,000 students and unlock the power of Excel to utilize its analytical tools - no matter your experience level. Master advanced Excel formulas and tools from Vlookup to Pivot Tables, create graphs and visualizations that can summarize critical business insights, and utilize Data Analysis ToolPak for descriptive and regression analysis. Gain a competitive advantage in the job market. WHY WOULD YOU CHOOSE TO LEARN EXCEL?Excel is one of the most widely used solutions for analyzing and visualizing data. Excel in itself can do so much for your career. It's just one program but it's the one hiring managers are interested in. Advanced Microsoft Excel skills can get you a promotion and make you a rock star at your company. WHY TAKE THIS SPECIFIC EXCEL COURSE?This course is concentrated on the most important tools for performing data analysis on the job. In this course you'll play the role of data analyst at a delivery company and you'll be working with real-life data sets. You don't need to spend weeks and months to learn Excel. As you go through the course, you'll be able to apply what you learnt immediately to your job. Author of this course has over 10 years of working experience in large financial organizations and over 5 years of experience of online and in-person trainings. He has dozens of courses on Excel, SQL, Power BI, Access, and more than 20,000 students in total. Surely he knows what you need. HERE WHY THIS COURSE IS ONE OF THE BEST COURSES ON UDEMY:★★★★★ Rashed Al NaamaniProbably this is one of the best course I have done for Excel... instructor pace is very good and clearly explain each tool in details. Thumbs up?★★★★★ Sonika SharmaEXCELLENT WORK!! REAL EXPERIENCE WITH REAL DATA SIMULTANEOUSLY WHILE LEARNING. GREAT!!! GREAT!!! GREAT!!!! GREAT!!!★★★★★ Vardan DanielyanVery detailed, extremely well explained, useful information and tricks. Excel is great for organizing and presenting data, and this course has everything you might need to work with Excel, and learn all nuances. Totally recommend!★★★★★ Urs FehrThe structure of this course is very well done with high quality information, and rounded off with how to put the theory into practice with practical examples. This instructor has gone onto my favorites list. Thanks a lot. WHAT ARE SOME EXCEL TOOLS AND FUNCTIONS YOU WILL LEARN IN THIS COURSE?You'll learn:· How to clean and prepare data by Sort, Filter, Find, Replace, Remove Duplicates, and Text to Columns tools.· How to use drop-down lists in Excel and add Data Validation to the cells.· How to best navigate large data and large spreadsheets.· How to Protect your Excel files and worksheets properly.· The most useful Excel functions like SUBTOTAL, SUMIF, COUNTIF, IF, OR, PMT, RATE, MEDIAN and many more.· How to write advanced Excel formulas by VLOOKUP, INDEX, MATCH functions.· How to convert raw Excel data into information you can use to create reports on.· Excel Pivot Tables so you can quickly get insights from your data.· Excel charts that go beyond Column and Bar charts. You'll learn how to create Combo charts, Histogram, Scatter Plot, Speedometer charts and more.· How to create interactive dashboards in Excel by using Slicer and Pivot Charts.· How to activate and use Data Analysis ToolPak for advanced statistical analysis.· Work in Excel faster by using hot key shortcuts.· Make homework and solve quizzes along the way to test your new Excel skills. WHAT ABOUT CERTIFICATE? DO YOU PROVIDE A CERTIFICATE?Upon completion of the course, you will be able to download a Certificate of completion with your name on it. Then, you can upload this certificate on LinkedIn and show potential employers this is a skill you possess. So, what are you waiting for? Join today and get immediate, lifetime access to the following:· 5+ hours on-demand video· Downloadable project files· Practical exercises & quizzes· 1-on-1 expert support· Course Q & A forum· 30-day money-back guarantee· Digital Certificate of CompletionSee you in there! Sincerely, Vardges ZardaryanP. S. Looking to master the full Microsoft Excel, Power BI + SQL stack? Search for Vardges Zardaryan and complete the courses below to become a Data Analysis Rock Star:1. Mastering Data Analysis in Excel2. Mastering Data Analysis with Power BI3. Data Analyst's Toolbox: Excel, SQL, Power BI4. The Complete Introduction to SQL for Data Analytics...

9. Mastering Data Structure Using C

4.1

(74)

As applications are getting complex and data rich, there are three common problems that applications face now-a-days. Data Search − Consider an inventory of 1 million(106) items of a store. If the application is to search an item, it has to search an item in 1 million(106) items every time slowing down the search. As data grows, search will become slower. Processor speed − Processor speed although being very high, falls limited if the data grows to billion records. Multiple requests − As thousands of users can search data simultaneously on a web server, even the fast server fails while searching the data. To solve the above-mentioned problems, data structures come to rescue. Data can be organized in a data structure in such a way that all items may not be required to be searched, and the required data can be searched almost instantly...

10. Master SQL For Data Science

4.6

(12,926)

LAST UPDATED: November 2022This course will turn you into a SQL query wizard. You'll learn the skills you need to extract critical insight from data sitting in a database. There are over 100 puzzles scattered throughout the course with in-depth solutions providing plenty of opportunity for you to practice. After completing the course and all of it's assignments, I promise you, you'll never be afraid to look at a large SQL query again. Just like my other courses, I follow the no-student-left behind principle; which means that I start from the very basics. You do not need any prerequisites to take this course. We move step by step into more advanced topics as we delve into the world of advanced querying techniques using subqueries, aggregations, joins, rollups and cubes, window functions, transposing & ranking data and using conditional expressions in very interesting ways. With over 17,000 students and a 4.6 rating, you won't find a better source to learn SQL for Data Science elsewhere. Don't just take it from me, take it from other students that have taken this course.★★★★★ Here's reviews from real students that took this course ★★★★★★★★★★ You really can't beat this course for the value. The instructor is excellent (clear explanations, easy to understand, extremely knowledgeable), and his style of constantly requiring the student to apply what they've just learned with practice queries proves to be a very effective method of learning. He covers an amazing amount of ground in just 9 hours. It was just the refresher course I needed after not having done much SQL in the past year.★★★★★ Just one word - Exceptional!! Don't give a second thought, just go for it. Thanks a lot Mr. Imtiaz Ahmad. The way concepts are explained in the lectures are quite good. The assignments gave me so much confidence and I feel so happy that I am quite well versed in SQL now. Watch the videos, try out the assignments on your own and practice as much as you can with different problems.★★★★★ It's a brilliant course that can help to understand SQL from easy concepts to difficult tasks. Besides, the explanations are always clear, so they let me learn a lot without searching for additional information in Internet. The course contains lots of practical tasks that allowed me not only to understand queries, but to also use them correctly.★★★★★ Great! I really like the exercises that are included. They are essential to learning the course content.★★★★★ After attending the course and doing most of the exercises, I feel very confident in SQL world. The course is designed well and every lesson gives you good amount of knowledge. Explanation and exercises are worth learning and practicing. Topics covered in this course: What is a DatabaseInstalling PostgresCreating TablesSELECT StatementWHERE ClauseAND & ORFiltering OperatorsORDER BYLIMITDISTINCTRenaming ColumnsFunctionsGROUP BY & HAVING ClausesAggregation QueriesSubqueriesCASE ClauseCorrelated SubqueriesTable JoinsINNER and OUTER JoinsUNION, UNION ALL and EXCEPT ClausesWindow Functions for Analytics+ over 100 puzzles distributed throughout the courseEnroll today to become a Master SQL Data Science Developer. As always, I offer a 30 day money back guarantee if you're not satisfied, but you won't need it...

11. Mastering data visualization in D3.js

4.5

(5,057)

Welcome to Mastering data visualization in D3. js! This course will take you from a beginner level in D3 to the point where you can build virtually any visualization that you can imagine. The course will teach you to program in the latest version of D3 - version 6. x. Course OutlineIn the first phase of the course, I will be building up your knowledge of D3 and introducing you to some of the most foundational topics in data visualization. You will: Understand what SVGs are and how to they work with D3. Discover how D3 associates shapes with pieces of data. Write scales, axes, and labels to make some basic visualizations. Use the D3 update pattern to shift the position of SVGs as our data changes. Handle user interactions by adding events to the page. Add legends, tooltips, and sliders to your visualizations. The course will also focus on data visualization design, helping you to make better decisions about how to structure your code, and teaching you to justify the decisions that you make to others. You will learn how to select the right visual channels for the data that you're working with to create completely unique visualizations. In the second phase of the course, I will be taking you on a crash course through 12 new visualizations. You will gain a wide breadth of knowledge in D3, as I will be walking you through pre-written code from members of the D3 community. I'll introduce you to D3 layouts, and I will be showing you how to build each of these visualizations in D3: Line ChartsArea ChartsStacked Area ChartsPie ChartsDonut ChartsWordcloudsChoropleth MapsNode-Link DiagramsTree DiagramsTreemapsCircle PacksSunburst PlotsThis part of the course will also teach you the skill of finding new visualizations by yourself, adapting open source code to fit with your own data. In the final phase of the course, I will be showing you the proper file structure to use for managing multiple visualizations on the page at once. You will be able to create visualizations that can communicate with one another, allowing you to link user interactions between multiple different graphs. You'll also learn how to use brushes in D3 to select areas on the chart with the drag of a mouse. Class ProjectsThe course will include 4 class projects for you to complete, which will give you the opportunity to practice your D3 skills with real data: A simple bar chart to display the revenue growth of a small coffee chain. An updating bubble chart, cloning a famous visualization from Gapminder. An interactive line chart, showing historical cryptocurrency prices over time. A data dashboard for a large conglomerate company. Each of the projects will gradually become more complex as the course progresses. Should I Take This Course?D3 is an incredibly powerful library to use, with a strong community of developers which is growing every day. Students should take this class if they want to get a rigorous introduction to D3, which covers a wide range of different topics. This course is not an introductory course to web development. Students are expected to have had experience coding in JavaScript, HTML, CSS, and jQuery before enrolling in this course...

12. Mastering Data Visualization: Theory and Foundations

4.6

(1,416)

Welcome to Mastering Data Visualization! In this course, you're going to learn about the Theory and Foundations of Data Visualization so that you can create amazing charts that are informative, true to the data, and communicatively effective. Have you noticed there are more and more charts generated every day? If you turn on the TV, there's a bar chart telling you the evolution of COVID, if you go on Twitter, boom! a lot of line charts displaying the evolution of the price of gas. In newspapers, lots and lots of infographics telling you about the most recent discovery. The reason for that is that now we have lots of data, and the most natural way to communicate data is in visual form: that is, through Data Visualization. But, have you noticed all of the mistakes in those visualizations? I have to tell you, many of the charts that I see regularly have one problem or another. Maybe their color choices are confusing, they chose the wrong type of chart, or they are displaying data in a distorted way. Actually, that happens because more and more professional roles now require to present data visually, but there's few training on how to do it correctly. This course aims to solve this gap. If there's one thing I can promise you is that, after completing this course, you'll be looking at charts at a completely different way. You will be able to distinguish good and bad visualizations, and, more importantly, you will be able to tell when a graph is lying and how to correct it. If you need to analyze, present or communicate data professionally at some point, this course is a must. Actually, even if you don't need to actually draw plots for a living, this course is hugely useful. After all, we are all consumers of data visualizations, and we need to identify when charts are lying to us. (As an example, my mother attended one of my classes and now she's spotting mistakes in a lot of the media she sees everyday!)I really encourage you to deepen your knowledge on Data Visualization. It's not a difficult topic, and we will start from the basics. You don't need any previous knowledge. I'll teach you everything you need to know along the way and we'll go straight to the point. No rambling. I really hope to see you in class!...

13. Informatica Master Data Management Hub Tool

4.3

(565)

The Informatica Master Data Management Hub Tool course is for beginners who would like to start their career as MDM Developer or MDM Administrator. The course focuses on various features of MDM hub and how to use those for successful implementation of MDM Solution. At the end of this course, you should be able to -Access SQL Developer, Jboss Application Server and MDM hubRegister Operational Reference Store (ORS) in MDM hubValidate ORSCreate Party Data modelCreate Users and assign Operational Reference Store and Master DatabaseAssign MDM hub tools to UsersConfigure Source SystemsCreate Landing, Staging and Base Object TableConfigure Delta Detection and Raw RetentionCreate Cleanse functionsCreate mappings between landing and staging tablesConfigure relationships and LookupConfigure Trust values to Source SystemsConfigure Match and Merge RulesCreate queries and packagesConfigure roles and privilegesConfigure batch groupsExecute batch jobs...

14. Mastering Data Analysis with Power BI

4.5

(154)

Join to over 5,000 students and learn all essential tools and techniques for business data analysis and visualization in Power BI. Become an expert of Power BI in a short period. Learn how to turn raw data into business insights and make data-driven recommendations by Power BI. Gain a competitive advantage in the job market. WHY WOULD YOU CHOOSE TO LEARN POWER BI?Power BI is quickly gaining popularity among professionals in data analysis as a cloud-based service that helps them easily visualize and share insights from their organizations' data. Advanced Power BI skills can get you a promotion and make you a rock star at your company. WORRIED THAT YOU HAVE NO PREVIOUS EXPERIENCE?Not an issue. We will start from the very basics and gradually teach you everything you need to know. Step by step. With no steps skipped. WHY TAKE THIS SPECIFIC POWER BI COURSE?This course is concentrated on the most important tools for performing data analysis on the job. In this course you'll play the role of data analyst at a delivery company and you'll be working with real-life data sets. You don't need to spend weeks and months to learn Power BI. As you go through the course, you'll be able to apply what you learnt immediately to your job. Author of this course has over 10 years of working experience in large financial organizations and over 5 years of experience of online and in-person trainings. He has dozens of courses on Excel, SQL, Power BI, Access, and more than 20,000 students in total. Surely he knows what you need. If you want to take your skills of data analytics to the next level, this course is definitely for you. HERE WHY THIS COURSE IS ONE OF THE BEST COURSES ON UDEMY:★★★★★ Alex KapogiannisVery informative and nicely paced, suitable for every level of user! Course gives you all around knowledge of the subject, very good for building up confidence on handling and mastering Power BI. Keep up the good work!★★★★★ Francis Mwangangi KivutiThe explanation are clear and the examples match real life scenarios★★★★★ Vardan DanielyanThis is an excellent course for beginners as well as intermediate and advanced users. It breaks down some important concepts in a manner that is clear and understandable for problem solving. The course is very detailed and well explained. It is invaluable both for learning and for reference. With a lesson approach it is easy to learn, practice and gain some mastery. WHAT ARE SOME POWER BI TOOLS AND FUNCTIONS YOU WILL LEARN IN THIS COURSE?You'll learn:· How to connect different types of data to Power BI.· How to organize, clean and manage data in Power BI.· How to create relationships between different data sets in Power BI.· How to best navigate large data and large spreadsheets.· Power BI charts that go beyond Column and Bar charts. You'll learn how to create Combo charts, Gauge, Map, Waterfall, Treemap, Histogram charts and more.· How to create interactive dashboards in Power BI by using Slicer.· How to set up automatically update of your dashboards based on external data updates.· How to publish your project to Power BI Service.· Make homework and solve quizzes along the way to test your new Power BI skills. WHAT ABOUT CERTIFICATE? DO YOU PROVIDE A CERTIFICATE?Upon completion of the course, you will be able to download a certificate of completion with your name on it. Then, you can upload this certificate on LinkedIn and show potential employers this is a skill you possess. So, what are you waiting for? Join today and get immediate, lifetime access to the following:· Downloadable project files· Practical exercises & quizzes· 1-on-1 expert support· Course Q & A forum· 30-day money-back guarantee· Digital Certificate of CompletionSee you in there! Sincerely, Vardges ZardaryanP. S. Looking to master the full Microsoft Excel, Power BI + SQL stack? Search for Vardges Zardaryan and complete the courses below to become a Data Analysis Rock Star:1. Mastering Data Analysis in Excel2. Mastering Data Analysis with Power BI3. Data Analyst's Toolbox: Excel, SQL, Power BI4. The Complete Introduction to SQL for Data Analytics...

15. Informatica Master Data Management Concepts (MDM)

4.3

(956)

The Informatica Master Data Management Concepts course is for all levels who would like to enhance their knowledge about Informatica MDM Developer. The course focuses on various features of the MDM hub and how to use those for the successful implementation of MDM Solution. If you are planning to start your career as Informatica Developer or would like to clear your Informatica MDM concepts then this course will be the best start. This course will also act as the foundation course for Informatica MDM Certification.  This introductory course will help to understand various concepts in the Informatica Master Data Management (Informatica MDM).  At the end of this course, you should be able to learnMDM Architecture MDM FrameworkTables in MDM such as Landing Tables, Staging Tables, and Base Object tablesMatch Column configurationMatch Rule SetupUnderstanding Exact and Fuzzy matchStage, load, and Match-Merge jobsRaw Retention at Stage TableDelta Detection processTokenizationConsolidation ProcessIn this course, we will be using Informatica MDM hub tool for demonstration. For hands-on practice, you need to have Informatica MDM Hub installed in your system. The advanced courses such as Business Entity Services, Entity 360, Active VOS Designer, Services Integration Framework (SIF), Informatica Data Director (IDD) will be covered as part of the separate courses...

16. Core Data and Realm - Master Data Persistence for iOS

4.1

(348)

Do you have an idea for an app that needs to save user data locally? Do you need to learn about Core Data for your work or business? Are you looking to brush up on your iOS Development skills by learning about new technologies such as Realm Database? Then this is the course for you! Join me as I take you step-by-step through building a to do list app that's like the Clear app. Along the way, we'll cover all the essential topics such as: How to Use Core DataHow to Use Realm DatabaseHow to Properly Set Up a Project with Core DataHow to Incorporate Realm Database Using CocoapodsHow to Build a To Do List AppHow to Save User Data Locally to the iPhoneiOS SandboxingiOS Backend Options and DatabasesHow to Store Data Using the iOS File System and NSCoderHow to Use UserDefaults Properly and much much more. Take a look at what other students have been saying about this course: I am about a third through this course and I have learned so much. This course is worth way more than what it cost but I'm thankful prices are low or I might have passed it up in the first place not knowing what I would get. I have used a couple Udemy courses and countless youtube tutorials. This is the best course I've ever took. - Jeffrey Nelson The course offers interesting concepts coupled with a teacher that explains things clearly. You get to make a bunch of interesting apps and expand your skills. Thanks Angela! - Megan Eding Clear tutorials, the lecturer explains everything well. It is one of the best courses I have participated in on Udemy. - Mark Garcia Angela is connecting the missing dots for me.- Tom Colenbrander What are you waiting for? Join the course today!...

17. Master Data Analysis with Python - Selecting Subsets of Data

4.6

(81)

Master Data Analysis with Python - Selecting Subsets of Data targets those who want to completely master doing data analysis with pandas. This is the second course in the Master Data Analysis with Python series and provides extremely detailed coverage of how to do any type of subset selection within a pandas DataFrame or Series. Exercises and a Free Certification ExamOver 100 exercises with detailed solutions are available for you to practice. Additionally, there is a free challenging certification exam offered for those who want to validate their knowledge gained. Expert InstructorThis course is taught by expert instructor Ted Petrou, author of the highly-rated text books Pandas Cookbook and Master Data Analysis with Python. Ted has taught over 1,000 hours of live in-person data science courses that use the pandas library. Pandas is a difficult library to use effectively and is often taught incorrectly with poor practices. Ted is extremely adept at using pandas and is known for developing best practices on how to use the library. All of the material and exercises are written in Jupyter Notebooks available for you to download. This allows you to read the notes, run the code, and write solutions to the exercises all in a single place. Become an ExpertThis course targets those who have an interest in becoming experts and completely mastering the pandas library for data analysis in a professional environment. This course does not cover all of the pandas library, just a small and fundamental portion of it. If you are looking for a brief introduction of the entire pandas library, this course is not it. It takes many dozens of hours, lots of practice, and rigorous understanding to be successful using pandas for data analysis in a professional environment. The Master Data Analysis with Python SeriesSelecting Subsets of Data is second in the Master Data Analysis with Python series which includes the following sequence of courses: Intro to PandasSelecting Subsets of Data with PandasEssential Pandas CommandsGrouping Data with PandasTime Series with PandasCleaning Data with PandasJoining Data with PandasData VisualizationAdvanced PandasExploratory Data AnalysisThis course assumes no previous pandas experience. The only prerequisite knowledge is to understand the fundamentals of Python...

18. Mastering Data Analysis with Pandas: Learning Path Part 3

In this structured series of hands-on guided projects, we will master the fundamentals of data analysis and manipulation with Pandas and Python. Pandas is a super powerful, fast, flexible and easy to use open-source data analysis and manipulation tool. This guided project is the third of a series of multiple guided projects (learning path) that is designed for anyone who wants to master data analysis with pandas. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions...

19. Mastering Data Analysis with Pandas: Learning Path Part 5

In this structured series of hands-on guided projects, we will master the fundamentals of data analysis and manipulation with Pandas and Python. Pandas is a super powerful, fast, flexible and easy to use open-source data analysis and manipulation tool. This guided project is the fifth of a series of multiple guided projects (learning path) that is designed for anyone who wants to master data analysis with pandas. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions...