Last Updated on December 28, 2022
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how to learn data modeling
How to Learn Data Modeling: Find the Best Data Modeling Training Online
For a business to be successful, its operations must be seamless. Data models, or database models, provide an easy framework for businesses to store and retrieve information. To learn data modeling, you must have an open mind and enough time to dedicate to study. It is a skill that can put your business on the map.
This guide will cover all the resources you need to learn this new skill. There are online courses, books, and tutorials that will bolster your learning process. Utilizing data modeling is integral for modern businesses, from small organizations to Fortune 500 companies.
What Is Data Modeling?
Data modeling is the process of creating a model to store data in a database. It is a visual representation of data that illustrates the connection between different types of information, including their structure and organization.
If you want to become a database administrator, you should be familiar with data modeling. It uses standard schemes and formal techniques to provide a consistent data resource. Businesses can then utilize predictive analytics to make accurate predictions using the data by defining and managing it to benefit the organization as a whole.
Data modeling can take different forms depending on the needs of a particular business. The goal of the data collection is usually determined by a company’s stakeholders. The information can be stored and used to generate reports when necessary. Data models are shared among a company’s partners, vendors, and industry peers.
What Is Data Modeling Used For?
Data modeling is a combined effort by the business side and the IT team in an organization. Developers, business analysts, and data architects can view a database and use it to draw accurate conclusions. Below are a few reasons why data modeling is essential.
- Reducing risk. As the amount of data available to a company increases every day, organizations are faced with a challenge. The data being collected must be kept simple and low risk to avoid issues.
Data modeling provides reliable diagrams for data processes so that the full architecture of the data can be reviewed. By viewing all of the data, a company can protect certain data by curtailing employees’ access to it.
- Improving collaboration. It is much easier for the IT team to collaborate with non-technical staff if a data model is in place. Businesses can use the system to integrate business processes, data structures, data rules, and implement physical data.
- Streamlining business processes. Data modeling can help a business better understand its operations. The information gathered can provide a clear view of a customer base, which can bring to light areas in need of improvement. Boosting customer relationships and engagement can then stimulate growth.
- Reducing expenditures. Data modeling ensures that a company’s processes are streamline, which allows ease of business. You will be able to spot errors quickly when using a data model, which can significantly reduce costs.
Types of Data Models
There are many different data models available, the most common of which is the relational model. Let’s look at some of the widely used models below.
The basis of this model is a tree-like structure that has records stemming from roots that grow into leaves. It is a common way to store information in a real-world scenario. It is utilized by companies such as IBM and in the creations of website sitemaps.»
It is one of the simplest models to use. Any change made on the parent node affects the child node, which improves the integrity of the data.
Relational Data Modeling
The model maintains data in a two-dimensional table. The structure of the model is tables, which are typically referred to as relations. The rows of this model are called tuples.
The column represents the attribute of an entity, and the row represents the records. It is simple, scalable, and structurally independent.
This model uses diagrams to depict the different elements in a database. It contains entity sets and relationship sets. It is an effective communication tool that can be transferred to any other model.
The network model is quite similar to the hierarchical model. The only major difference is that in this case, a record can have more than one parent. Also, instead of a tree, this model uses a graph to represent information. Data can be easily accessed in this model because it can be obtained from more than one path.
Learning Data Modeling
There are many materials online that you can turn to as you learn data modeling, but choosing the best ones can be a challenge. Data modeling is an excellent skill to have, but it must be acquired through the proper channels. Below, you will find a list of online resources that will be instrumental in helping you study.
How Long Does It Take to Learn Data Modeling?
The time it takes to learn any skill can’t be set in stone. Everyone will take a different amount of time to complete a course or finish their self-paced studying. An expert in data science may be able to fully learn data modeling in a matter of weeks. However, it may take months for a novice to fully grasp the concepts of this topic.
People with more free time to dedicate to learning may be able to complete a course in just a few days. But if your schedule is cramped, it will take much longer.
How to Learn Data Modeling: Step-by-Step
Below are some simple steps you should follow as you start learning about data modeling.
- Purchase and install tools. There are many tools available online for data modeling. You may choose to download Erwin Data Modeler, Oracle SQL Developer Data Modeler, or Archi.
- Watch data modeling tutorials. You can check out some data modeling tutorials to help you gain a deeper understanding of the practice. These tutorials are instrumental in ensuring you learn the processes correctly.
- Sign up for classes. There are classes on data modeling available worldwide, including physical classes and online options. You may want to consider an online class until the Coronavirus subsides.
- Read books. There are many books out there on data modeling that will offer information that can help you gain more insight into the various models, and their benefits and uses.
- Practice. Remember that to become a good data architect, you must continually practice.
The Best Data Modeling Courses and Training
Deciding to enroll in a class or training course is key to becoming a data scientist. Increasingly more organizations are seeking to hire people with technical knowledge of data modeling techniques. Businesses are now relying on data modeling strategies to improve their profit margins.
From the courses below, you should select one that matches your preferred type of learning as you learn more about data modeling.
Best In-Person Data Modeling Classes
Having an instructor available is the ultimate resource for any student. Some people find it easier to study in a classroom where you can get one-on-one time with your teacher. This makes it easier to clear up any questions you have about new terms or mind-boggling concepts.
IBM Data Analyst Professional Certificate
- Provider: IBM
- Time: 10 months
- Prerequisites: N/A
- Cost: Free
This is an exceptional course for people who want to improve their skills. By the end of the course, you will have a good understanding of the data programming language SQL, spreadsheets, pivot tables, data science, and how to program with Python. Students will be proficient in using spreadsheets, creating versatile charts, and describing data ecosystems using SQL, Python, and Jupyter Notebooks.
Big Data Modeling and Management Systems
- Provider: University of California, San Diego
- Time: 13 hours
- Prerequisites: Quad Core Processor, Apache Hadoop
By the end of this beginners’ course, you will be able to perform several functions using the data modeling software Hadoop. You will be able to differentiate between types of data, use a logical data model, identify frequency, and design big data systems. You can sign up for a more advanced course after completing this level.
Best Online Data Modeling Courses
Online classes are a good way to pick up any new skill. Let’s look at some of the best online options for learning data modeling.
Mastering Data Modeling Fundamentals
- Provider: Udemy
- Time: 13 hours
- Prerequisites: N/A
- Cost: $9.99
In this course, students will master the techniques needed to build data models. The lessons will cover hierarchies, relationships and attributes, entity types, and entity-relationship models. Students will also learn more about key data modeling designs, data points, foreign keys, primary keys, and how to convert conceptual data models into logical or physical data models.
Databases: Modeling and Theory
- Provider: EdX
- Time: 2 weeks
- Prerequisites: N/A
- Cost: $50
This is a self-paced course that involves learning about relational databases and SQL, OLAP and recursion, as well as modeling and theory. All the classes are based around video lectures and video demos, to make sure students get a firm grasp of the material. Each course also includes extra reading material, quizzes, and other resources.
Data Science: Inference and Modeling
- Provider: Harvard University
- Time: 8 weeks
- Prerequisites: N/A
- Cost: $99
In this course, students will learn about how to use inference and modeling to develop statistical approaches. The course teaches all the necessary concepts to help you define margins and errors. Additionally, you will learn the basics of Bayesian statistics and models that are used to aggregate data from multiple sources.
“Career Karma entered my life when I needed it most and quickly helped me match with a bootcamp. Two months after graduating, I found my dream job that aligned with my values and goals in life!”
Using Excel for Financial Modeling
- Provider: Harvard University
- Time: 8 weeks
- Cost: $99
In this LinkedIn learning course, the instructor will teach you how to make informed decisions using data analytics. You will learn how to build models for use in corporate finance, investment banking, commercial banking, and portfolio management.
Best Free Data Modeling Courses
You don’t have to shell out a lot of money to be able to include data modeling on your resume. Below is a free course you can take to get started.
Data Modeling and Regression Analysis in Business
- Provider: University of Illinois
- Time: 25 hours
- Prerequisites: Intermediate data modeling experience
- Cost: Free
This is an excellent course for business managers who want to get equipped with data description, statistical inference, and regression.
The following is a step-by-step guide to data modeling in BI Office as described in the overview.
The wizard displays a series of panels to guide you through the process of importing and processing data into an analytic data model that can be analyzed in Data Discovery and then presented as a Story Board or Publication.
To begin, go to the Start page, click the yellow “New Data Modeling” button to launch the Data Modeling wizard (described here).
Step 1: Choose a Data Source
The data source options are displayed in the left-hand panel (blue arrow).
For each data source, the available options are shown on the right hand side. For example, the ability to upload an excel file is provided (green arrow). You can add multiple items from multiple data sources per model.
The data source options include file-based or local sources, configured sources (ie server databases and cloud sources), BI Office content and packaged sources.
Step 2: Selection of Data Sets
After selecting data sources, you are presented with a selection of potential data sets (tables) for each data source.
Select which data sets (orange highlight) that will be included in the final model. As you add new data sets (tables), the data flow graphic on the right will show the movement of the data to the model.
- Clicking a table icon (green highlight) will show a sample of its data (by the blue arrow).
- Clicking a filter (black highlight) will allow you to filter the data set before its added to the model.
- Clicking the schedule icon (purple highlight) will allow you to set a refresh schedule for the raw data import into the model
NOTE: for some data source types you can provide a custom script to build the data set using a run-time query of the data source (red arrow).
Click here for more on data set and table selections.
Step 3: Selection of Attributes, Columns and Metrics
For each data set or table selected previously, you can see a list of all its ‘attributes’ or columns (orange highlight). These columns will be used in your data mode to slice and dice your information. They will also be used to generate the metrics or “measures” of the data model (green highlight).
Beyond selecting which columns will be used and made visible in the data model, there are numerous other settings related to sorting, categorization and folder grouping that can be set for each column in the data set. Other capabilities include merging and splitting of column data to create more useful data constructs in the discovery application. The wizard will also allow users to generate ‘calculated’ columns using formulae to either create column values or derive them from other existing columns in the source data set.
An important feature of the column selection phase is the ability to define metrics for analysis using data in columns. This includes selecting metric columns, setting their formats and aggregation types. Where needed multiple metrics or measures can be set for each column and new calculated measures can be created from existing column data.
Click here for more on column selections.
Click here for specifics on model measures.
The “Relationship” tool provides an opportunity for users to review, edit and add any connections or “relationships” between your different data sets and tables. This critical step allows you to “mash-up” the different data sets and glue them together for analysis.
The Data Model engine will extrapolate any relationships that already exists, and highlight them in orange. Using the heuristics slider (purple highlight), the engine will attempt to auto-match and determine relationships between the tables for you in red. Alternatively, you can drag and drop the relationships using the mouse to manually create the “lines” in between the tables.
Use the table view toggle buttons (orange highlight) to see table details.
Click here for more details on the relationship tool
Step 5: Hierarchies
You can optionally add drill-down trees or “hierarchies” to your model to simplify the data navigation in Data Discovery.
NOTE: Hierarchies can also be added directly from inside the Data Discovery while analyzing the model after the model is built.
The hierarchy editor will show you a list of columns per data set (orange highlight) – on the left; that can be combined to create the hierarchy drill path – in the middle.
Give the hierarchy a name (blue highlight) and then, once you have built the path, click the green add button (red highlight) to add it to the existing hierarchy listing on the right.
NOTE: The time intelligence option will automatically create relevant hierarchies for you. You can elect to edit these or remove them.
Click here for more on creating hierarchies.
Step 6: Roles & Permissions
The wizard displays the roles and permissions for accessing your data model. From here, you can allow which others in your own groupings can manage and see your model (and which ones cannot). By default, you will always be able to see and manage your own model unless the administrator changes them manually on the backend.
NOTE: The viewable roles reflect the role groupings that you already belong to. Administrators can manually expand this listing through the backend.
Click here for more on securing your data model.
Step 7: Finalization and Deployment
In the last step you need to provide a Model’s Name and Description.
You also need to make a few elections related to the destination server (purple arrow) that will host your model and other default choices (blue highlight). If you are using packages, there will be other choices related to matching reports for the packaged models.
NOTE: Your destination host server list is set from the administrative console.
Clicking finish will launch your model build and deployment job to the server, which will begin the process of extracting the raw data, transforming it and loading it into the new data model on the host server.
You will be presented with a spinner which will be displayed for the duration of the processing cycle (which may take some time).
On completion, if you have elected to auto launch the model you will be directed into a Data Discovery session with your new model. Otherwise, you can then find the new model in the list of data sources on the host server when you start a new the Data Discovery session from the Start page.