How To Become a Data Modeler?
Last updated on 14th Oct 2020, Artciles, Blog
Logical data and process modeling are two essential first steps in the development of information systems, for both transaction processing and decision support (data warehousing). But how do you learn to be a modeler? How do you make sure the next information system you develop begins with the proper foundation?
The purpose of logical data modeling is to discover, analyze, define and standardize the discrete facts required by the business to conduct its activities. A data modeler must be concerned with both correctly interpreting the information needs of the business and providing organization and reusability to the resulting data entities and attributes. To accomplish this purpose, a modeling candidate must learn certain skills, techniques and rules, and apply those lessons rigorously and consistently. How best to learn is a matter of some debate, but there are some proven methods foreducating logical modelers that can be exploited and refined.
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Many people learn modeling “on the job” some study a book or use computer-based education, others attend a public class, while still others learn by watching an experienced modelerperform what seems like magic and attempting to imitate the practices of the mentor. Ultimately, the best way to learn and retain the knowledge and skills of data modeling is a combination of allthese methods. However, it is the order in which these methods are employed and the actual tools used that can separate a successful modeling educational experience from one that teaches thestudent very little or nothing.
What is a Data Modeler?
Data Modelers are Systems Analysts who design computer databases that translate complex business data into usable computer systems. Data Modelers work with data architects to design databases that meet organizational needs using conceptual, logical, and physical data models. Their models are designed to improve efficiency and outputs, and may focus on issues such as reducing data redundancy or improving data movement across systems.
Data Modelers work as part of team with other database administrators and data architects, usually as an employee of a large company or organization. Jobs for Database Administrators, including Data Modelers, are expected to grow in the coming years as the data needs of all companies continue to grow.
Data Modeler Duties and Responsibilities?
As they work to design and build useful databases, Data Modelers do a variety of different tasks. Here are some of the primary responsibilities Data Modelers have in their day-to-day work, based on job listing for this position.
Identify Business Needs
Data Modelers identify areas where data can be used to improve business activities, defining business users’ requirements. Then, using their understanding of data flows, they propose and implement innovative data solutions.
Create and Maintain Data Models
Data Modelers work closely with the database engineers to create optimal physical data models of datasets, then create and maintain data maps and systems interrelationship diagrams for data domains and systems
One of the Data Modeler’s responsibilities is to define and govern data modeling and design standards, tools, best practices, and related development methodologies for the organization for which they work. They also set standards for document naming, security, and lifecycle & retention architecture.
Based off of their data an analysis, Data Modelers make recommendations for standardization and proper data usage. They champion the usage of data in business, and communicate the benefits and return on investment for application and product owners.
Data Modeler Skills
An ideal Data Modeler is an analytical and creative thinker who is not intimidated by roadblocks and challenges. They understand how to successfully evaluate problems and develop appropriate solutions. Successful Data Modelers can also be counted on to perform well under pressure, possessing great focus while completing projects efficiently. They should be able to work well as part of a team, but also carry responsibility for their own work. Data Modelers also need to be able to work on multiple projects at a time, with the ability to quickly understand and incorporate new technologies. Below are some other skills and abilities that employers look for in a Data Modeler.
Core skills: Based on job listings we looked at, employers want Data Modelers with these core skills. Any aspiring Data Modeler should have these things on their resume.
- Expertise in data modeling principles/methods including conceptual, logical & physical Data Models
- Ability to clearly communicate complex technical ideas, regardless of the technical capacity of the audience
- Strong inter-personal skills and ability to work as part of a team
- Knowledge of the mathematical foundations of statistical inference and forecasting such as time series analysis, multivariate analysis, cluster analysis, and optimization
- Ability to quickly learn and adapt modeling methods from case studies or other proven approaches
Advanced skills: While most employers did not require the following skills, multiple job listings included them as preferred. If you can claim these skills, you will make a great candidate for a Data Modeler.
- Software Development experience
- Ability to utilize Business Intelligence tools (Power BI) to represent insights
- Experience working with dimensionally modeled data
- Experience in translating/mapping relational data models into XML and Schemas
Tools of the Trade: In their jobs, Data Modelers make use of a lot of high-tech tools to get the job done. Here are some of the tools that employers are looking for Data Modeler applicants to have experience with.
- Data analysis and modeling tools (e.g. Power Designer, ERWin, ER/Studio)
- SQL and/or PL/SQL
- RDBMS platforms (e.g. SQL Server, Oracle, Netezza, Teradata, DB2 / UDB)
- Microsoft Excel, Word, Power Point and Visio
Data Modeler Salary
Data Modelers are included under Database Administrators by the Bureau of Labor Statistics. According to the BLS, the median annual wage for Database Administrators is over $81,000. On the low end, Database Administrators may make less than $45,000 a year. The top earners in the field make more than $127,000 annually. The top three best-paid states for Database Administrators are New Jersey, District of Columbia, and Colorado, where they make median annual incomes of $105,000, $103,000, and $97,000, respectively.
Data modeling education does not assume much technical systems experience; indeed, a novice can become an excellent logical data modeler with no programming or systems administration experience.
Many data modeling professionals agree that programmers and systems administrators are not well-suited to be data modelers since the skills needed for logical data modeling (abstract thinking,conceptual design, user liaison, and communication, for example) are different from the skills developed in the programming and systems administration fields Basic requirements for a logical modeling candidate would include the proven ability to think abstractly and conceptually, to gatherrequirements from vague and often conflicting testimony, to demonstrate logical thought processes, and to communicate well, including–especially– to listen well.
Communication skills are essential for the data modeler, even with the proliferation of documentation software, because much of the job of logical data modeling involves the translating andbalancing of multiple user requirements and documenting the final results from the user perspective. A data modeler will usually present the completed model to an audience of users and databaseprofessionals, and write clear and concise documentation to support models and craft appropriate definitions. Modelers will also listen to the user(s) describe requirements, and must cull theimportant and relevant facts from the discourse.
Most novice modelers come from the business community. By taking experienced business people as modeling trainees, a company can capitalize on their business knowledge to assist in “filling in thegaps” during modeling education. It is extremely helpful for a novice modeler to understand the business being discussed and analyzed so the student is able to concentrate on learning datamodeling.
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The Learning Process
At the start of a novice modeler’s training period, he or she is usually should be assigned to a mentor, unfortunately this is not always the case. Ideally this mentor should be a very experienced, modeler who has having had formal modeling training education and has also experienced having lived through “on the job” learning. If the mentor has also undergone some training in the educational development process, to be able to understand the needs of a student and to respond appropriately to those needs, and to develop the inherent skills of the novice in conjunctionwith those modeling techniques under study understands how to be a good teacher, then the novice will get an even better education.
Many organizations are accustomed to training by experience (“on the job”), and to some degree this “education” is a proper way to expand a person’s knowledge base in data modeling and subsequent software development. However, most training by education from experience is predicated on a foundation of knowledge, and with modeling most novices have no foundation upon which tobuild.
A better use of the student / novice’s initial time and energy could be spent studying a Computer-Based-Training program (CBT) that focuses on computer-based education teaching the concepts elements of data and how understanding those elements in any business situation is “data modeling.”
Using the power and convenience of computer-based education is one of the better ways novice modelers can become exposed to the techniques used in discipline of logical modeling; experiential training demonstrates method for using that basic education to solve actual modeling problems. The case situations presented in a well-developed CBT course should form a progression of degrees of difficulty as well as ensure that the concepts of prior lessons are reinforced. For a novice modeler with little or no data modeling experience, beginning their course of study with such a CBT course is advisable.
However, CBT courses are taken in a vacuum, and if the mentor with actual modeling projects does not fully reinforce the lessons taught in the course, making the time invested in the CBT that education will not be fruitful. Each session of the computer-based education should be followed by an actual modeling mini-project for the student led by the mentor and drawn from an actual modeling project for the organization. This activity has several purposes: 1) to provide concrete experiential learning of the concepts under study, 2) to demonstrate the business requirements that are being modeled, and 3) to allow the students to solve modeling problems commensurate with their skill levels and to receive immediate results on their successful completion of the modeling assignment. The experiential learning exercise should be progressively more difficult, and if at all possible should occur in actual modeling sessions with users. This setting will also introduce the student to the facilitated sessions of data modeling discovery and will provide opportunity for the student to practice actual data requirements gathering with the mentor.
Most disciplines have formal courses that provide a student with the concepts and techniques of that discipline, and data modeling is no different. There are several good workshops/seminars that can train a student in the concepts and techniques of data modeling. Modeling courses are designed to prepare the student to successfully gather requirements, execute the modeling techniques, and document and discuss the models for users and technicians (programmers, DBA’s, etc.). These courses are most beneficial when they are coupled with the successful completion of CBT instruction computer-based education and mentored-driven performance.
Finding an appropriate course requires some diligence on the part of the student and their manager/mentor. To reduce some of the confusion and to assist in sorting through the details, the International Data Management Association (DAMA) has an Educational Services function, where under which recognized vendors and instructors can display their course outlines and overviews of the programs in a central location. Although DAMA International does not endorse any specific course(s), providing this central location of data management instructional information delivers a service to the ever-expanding field of data management/data administration. The DAMA I curriculum committee (part of the Educational Services function) is developing a comprehensive approach to IRM/DRM education, which willinclude data modeling as part of its foundation.
How Do You Become a Data Modeler?
A data modeler will often have a Bachelor’s Degree in a computer science field, statistical analysis field or even a marketing field. Data modelers often already have experience with data modeling solutions or with industries that are heavy on data collection and statistics. However, a data modeler does not necessarily have to have either education or experience: one can be used to compensate for the other. Career paths in online marketing may sometimes turn into data modeling careers, and the reverse can also be true. Data modelers may also have backgrounds in database administration, a fairly diverse field noted by O*Net Online to be growing.
Data modelers will most often work with consulting firms, but they can also work for the marketing and analysis departments of larger corporations. Data modelers that become very successful may be able to work on their own on a consultancy basis, but this occurs less often in the field of data modeling than in other IT fields.
How Do You Advance as a Data Modeler?
Data modelers can advance by being successful in their projects. A data modeler can eventually head their own department or become the manager of an IT firm that specializes in data modeling or data marketing. A modeler may also be able to work in a related field, such as online marketing, which have the potential for very high pay rates. Data modelers that work directly with a company may advance primarily based on seniority and the success rate of their projects. Overall, data modeling is a very broad field that includes entry-level positions as well as extremely specialized professional positions. One related field is the field of database analysis, which according to the Bureau of Labor Statistics features a high rate of pay and many job opportunities.
As one of the most important steps in the development of information systems, logical data modeling require specific skills and knowledge that can come from a variety of sources and methods of learning. Each situation will dictate the path(s) the student will follow, but a multi-disciplined approach offers the best opportunity to acquire the knowledge and skills necessary for a successful data modeling career.
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