Table of Contents
Introduction
Taking a new career path can be very challenging: you need a good roadmap to focus on industry-required skills, you need a recognized certification to prove your skills to employers, you need a strong community of like-minded people to advice and motivate you, you need to keep your current job; getting all of these is often difficult, but soon, it is not going to be enough as an excuse not to pursue a career in one of the most in-demand paths in the world right now: data analytics.
Next year, CompTIA is launching a new data analytics certification, CompTIA Data+ which aims to validate skills in data analytics and give a roadmap to new learners, but before we go deep into CompTIA Data+…
What Is Data Analytics
Organizations rely on data to make critical business decisions—which new products to develop, new markets to enter, new investments to make, and customers to target. They also use data to identify inefficiencies and other business problems that need to be addressed. Making sense of the collected data and using it to predict the future as well as influence the company’s next decisions is the job of data analysts; this sounds like a role every big company would need someone efficient to play, doesn’t it?
Data analytics is one of the top skills IT pros should have in 2021, and having this skill is vital to helping organizations reach conclusions that enable them to achieve better business results.
Only 25% of companies feel like they are exactly where they want to be with their corporate data management, down from 31% in 2015: this shows the world’s growing need for data analysts.
In an advancing world filled with data, pursuing a career in data analytics might be one of the wisest decisions to make in this age given companies severe need for data analysts
Data analysts are needed in almost every business, since every business predicts the future based on information they receive about their past products; it is therefore not surprising that data analytics is one of the most in-demand skills.
What Do Data Analysts Do?
Data analysts Collect, analyze and report on data through creating reports, dashboards and other visualizations associated with customers, business processes or market economics.
In a company, data analysts may have to analyze wjoch products should be produced in larger quantities to meet demands, which ones must be produced in lesser quantities to not record losses, all of this they do by analyzing customers.
Some of the roles of data analysts may include:
Developing and implementing databases and data collection systems
Acquiring data from primary and secondary sources
Cleaning and validating data
Data modeling design
Implementing new data analysis methodologies
Who Needs Data Analytics Skills?
Some job roles that require knowledge in data analytics include:
Data analyst: Data analysts collect, interpret and analyze data, and report results to key members of the organization.
Data scientist: A data scientist uses algorithms and scientific processes to extract information and insights from data to make decisions.
Reporting analyst: After gathering and analyzing data, reporting analysts prepare reports and provide suggestions for process improvement based on findings.
Business data analyst: Focusing on business operations data, this job role often bridges the gap between the technology realm and the business realm within the organization.
Business intelligence analyst: This role collects data internally and externally and compares the two to create a snapshot of the marketplace to help guide the organization to success.
Apart from those who have data-specific careers, other career paths can benefit from analytics processes and data analytics knowledge. Jobs like marketing specialists, financial analysts, human resource analysts or clinical health care analysts can optimize performance and make well-informed decisions when they use and evaluate data correctly.
Why You Need Data Analytics Skills
1. To better recognize patterns and trends.
Understanding trends and patterns is beneficial to any business owner; and even if you are not one yet, understanding trends would make you see openings and opportunities before others.
2. To understand how data is compiled.
It is the dream of every employee to become a business owner, but whatever business you venture into, you would need to know more about your potential customers; data analytics gives you the skills necessary to know how to get the right data from the potential customers.
3. To help your organization reach its goals.
Performance analysis is a path in data analysis where you can track measurements against defined goals and make suggestions to help achieve those goals.
4. To future-proof your career.
Only 44% of companies say that they have internal IT employees who are dedicated to data management or data analysis, and only 31% feel they have no more need for data analysts.
Certainly such promising careepath is something to look into.
Why CompTIA Data+
1. Certification
If you are developing analytics skills to bolster your personal business, you might not need a certificate, but if you are considering a career in data analytics, you certainly need an industry-standard certificate to validate your skills before potential employers.Â
CompTIA certifications have been around since 1993 and are arguably the oldest IT certification vendors, but don’t let the word ‘old’ deceive you! CompTIA upgrades each of its tests periodically to fit the current demands of the IT world and meet the industry standard.
CompTIA certifications hold ISO/ANSI accreditation status, which means they meet or exceed the global benchmarks set forth by ISO – the worldwide organization that sets the standard for certifications, processes, and products – and ANSI – the U.S. representative to ISO.
With this, you bypass the headache of having to think about a professional and industry-recognized certification in your new career.
2. Good Roadmap
The IT world is not a world that is often a very confusing one for beginners; you see a lot of enticing things along the way and sometimes you spend a long time jumping from one sector into another without having industry-standard knowledge in either sector.
With CompTIA certifications, you have a sense of direction; the certifications are graded in such a way that you know what should be next for you after finishing each one.
Also, while you are preparing, you are not just running around haphazardly in the IT world, but you are following a good structure that assures you that by the time you are done, you would have industry-standard knowledge.
3. Flexibility
While preparing for CompTIA certifications, you work at your own pace and can decide to strike a very good balance between work and learning, and advancing in your new career.
This ensures that you can easily advance in your studies, skills, and certifications without having to take time off from work. It serves as a good advantage over taking a degree course.
4. Community
CompTIA certification holders have formed a strong community you can learn from, interact with, ask for support from and give back to.
You have a community of like-minded people; people who have gotten the certifications you are working towards and can guide you towards making the best use of it when you get it and also the best way to get it.
If used wisely, the community could in fact be a bigger blessing than the certification itself, as you create connections that may have an enormous impact on your career and exposure.
What's On The Data+ Certification Exam?
According to CompTIA, Data+ exam objectives cover the skills required to transform business requirements in support of data-driven decisions by examining the following concepts:
1. Data Concepts and Environments
Identify basic concepts of data schemas and dimensions
Compare and contrast different data types
Compare and contrast common data structures and file formats
2. Data Mining
Explain data acquisition concepts
Identify common reasons for cleansing and profiling datasets
Given a scenario, execute data manipulation techniques
Explain common techniques for data manipulation and query optimization
3. Data Analysis
Given a scenario, apply the appropriate descriptive statistical methods
Explain the purpose of inferential statistical methods
Summarize types of analysis and key analysis techniques
Identify common data analytics tools
4. Visualization
Translate business requirements to form a report
Use appropriate design components for reports and dashboards
Use appropriate methods for dashboard development
Apply the appropriate type of visualization
Compare and contrast types of reports
Conclusion
With all of what CompTIA’s Data+ certification promises to offer, from flexibility and community support to good roadmaps and industry-standard certification in data analytics, it seems like a good enough reason to want to stay alive for one more year.
