How to Learn Data Analysis
Do you ever wonder how large-scale applications handle the enormous amounts of data that they generate? The scale of such applications requires powerful data storage set-ups as well as equally capable data processing sequences to get the best out of the data that they can acquire. Data Analysis is the process that defines how a business utilizes its data to help them get the most out of it.
In this guide, we’re going to talk about how to learn Data Analysis and what resources you can use to master it.
What You Need to Know About Data Analysis
Data Analysis involves sorting through enormous dumps of unstructured information to derive key insights from it. These insights are then utilized to enhance the various decision-making processes in organizations. During this process, various steps are employed to ensure that the results work out in the best interest of the business. Many times, a lot of time is spent polishing the data before modeling or visualizing it. To some, this might seem like overkill, but properly structured and cleaned data is known to present the best results of all.
The primary aim of data analysis is to churn out meaningful results from regular data. The most common practices used in the process are:
- Data Collection. Collecting the right amount and type of data is important in producing the correct results. Irrelevant or inadequate data can directly result in poor results irrespective of the efforts that you may put in the other steps of the process.
- Data Cleaning/Wrangling. The larger the data dump, the higher the chances of noise being present in it. Cleaning and wrangling are employed to remove the anomalous data that may hamper the results of the job.
- Data Manipulation. Data analysis requires a certain amount of data manipulation using popular tools such as Excel or Google Sheets. This manipulation helps convert the available fields into the desired features of the final model. This is, however, optional and can be done away with if you have the correct set of features in the initial dataset.
- Data Interpretation. When the data is finally prepared, the main step involves interpreting the data and identifying trends and anomalies. It is in this step where the major results start to stand out. The optimizations made further ensure that the best result possible is obtained.
- Data Visualization. The final step involved plotting the data in the form of a graph, chart, or any other form of graphical representation. This helps in presenting the data properly in reports or presentations and helps non-analysts understand the insights.
These are only a few of the many things the technology comprises. As you learn more about Data Analysis, you’ll become aware of more things you can use to help speed up your application’s development.
Skills Needed to Learn Data Analysis
To learn Data Analysis, you should have a basic understanding of information and data.
You do not need to be an expert in handling and managing data to understand Data Analysis well, but having an understanding of the two terms and their working will help you easily get started.
Why You Should Learn Data Analysis
If you are looking to make a career out of data analysis or data science, you need to know the basics of data analysis. Data Analysis is one of the most common methods for easily manipulating and gaining insights from business data. Even though data science takes things up a notch, data analysis is where most people start.
Due to its simple yet powerful data visualization techniques, data analysis is easy to carry out on all volumes of data. Considering the huge community backing data analysis, it is only wise to start your data journey using this technology.
How Long Does It Take to Learn Data Analysis?
The answer to this question depends on where you currently stand in data handling and processing. If you have some prior experience with tools like spreadsheet management software and data visualization software, one to two weeks should be sufficient to master the concepts used in Data Analysis. If not, you can expect a time of three to four weeks to cover the topics as well as tools in all their depth.
All in all, you can expect to devote four to six hours daily for a period of four to six weeks to get a good grip on the technology. To gain professional expertise, expect to spend about two to three months working on the ins and outs of the technology.
Learning Data Analysis: A Study Guide
You will find plenty of Data Analysis learning resources online. With so much information available, you may be wondering where exactly you should start. We have compiled a list of five learning resources to help you learn what you need to know about the Data Analysis platform.
- Resource Type: Written Tutorial
- Price: $51.82
- Prerequisites: Basic understanding of OOP programming or some experience in Python
Authored by the creator of the popular Pandas library in Python programming language, Python for Data Analysis takes a Python-first approach to handling, processing and analyzing data. The book is filled with a lot of examples at each step, and can help you find your way around data analysis easily if you have some prior experience in computer programming.
- Resource Type: Book
- Price: $28.01 (Amazon)
- Prerequisites: None
Written by veterans in the startup world, Lean Analytics can help you understand the importance of analytics and data with respect to real-life startups. The book is packed with over 30 case studies that deep dive into a set of companies and their analytics processes to help you understand the bigger picture better. If you are a beginner and are looking to build a startup soon, you will not want to miss out on this book.
- Resource Type: Certificate Course
- Price: Free
- Prerequisites: None
Offered by one of the top computer firms in the world — IBM — the data analyst professional certificate is a top-class certificate to complete if you are looking to hang around for long in the data science domain. The course will take about 11 months to complete if you are able to devote at least three hours of time per week. Although you can speed your way through, the above recommended pace allows you to get the best out of the available content.
The course is designed for a beginner, and involves a heavy amount of hands-on projects and labs to ensure that the learners are able to build a firm grasp on the technical skills required to carry out data analysis efficiently.
- Resource Type: Video Course
- Price: Free
- Prerequisites: None
Offered by the Imperial College of London, Data Analysis Essentials is a crash course for people of all experience levels on the various concepts and topics in data analysis. It keeps in mind the possibility of learners taking an MBA course right after completion, so a lot of the content is structured to help you prepare on an academic level.
While this course does not focus much on the professional applications of data analysis, you can still take it to ensure that your core fundamentals of the subject are strong, and that you do not find yourself googling every single thing when working on a real-time data analysis project.
- Resource Type: Video Tutorial
- Price: Free
- Prerequisites: None
Data Analytics Basic for Everyone aims to make the complex topics of Data Analysis super simple for beginners. Apart from focusing on the subject, this course also provides learners with an insight on how the career of a data analyst turns out to be. With this course, you get a peek into the lifecycle, career opportunities and learning paths that data analysts take throughout their career.
Communities for People Studying Data Analysis
Communities are an excellent resource for anyone who wants to learn Data Analysis. By joining a community, you can quickly find help. You can also learn more about how other people use Data Analysis, which may inform how you use the tool.
Below is a list of some communities for people learning Data Analysis that you may want to look at for more details:
Data Science Central is a premier community for data science enthusiasts and professionals. Users can log in and post any number of questions or discussions on the forum and can respond to the posts that they feel comfortable in. Apart from data analysis, other aspects of data science such as Big Data, Decision Science, and Predictive Analysis are also discussed here.
The Data Science Subreddit is a huge community of data science enthusiasts from all over the world. With over 444,000 members, you will always find somebody here who can solve your data analysis problems. The subreddit allows posting and responding to any thread created by any user. Similar to Data Science Central, this subreddit too is commonplace for everybody interested in data science as a whole, and not just data analysis.
How Hard is It to Learn Data Analysis?
Data Analysis is a fairly simple data processing technique to start using. You could feasibly put together a simple report on a standard data store with any popular data analysis tool within the very first week of learning. But to build more complex reports and draw detailed insights, you will need to devote a month or two to understand the fundamentals of the technology.
Additional features like cleaning and manipulation may not be needed very frequently, but it is worthwhile to learn them as well, as they add a layer of customization and ease of use to your data handling process.
Will Learning Data Analysis Help Me Find a Job?
Data Analysis is a highly sought-after database skill in the technology industry. Employers hiring for data analyst and scientist positions often list Data Analysis as an essential skill or an important qualification. To help you understand the value of learning Data Analysis for your career, we have compiled a few job and salary statistics.
- Salaries. PayScale reports that jobs that involve Data Analysis pay, on average, $67,755 per year. Positions that use this skill include data analyst, financial analyst, and data scientist.
- Industry Growth. According to the U.S. Bureau of Labor Statistics, information research scientists’ positions will grow at a rate of 14% through 2028. While not all of these positions will use data analysis, a considerable number of these professionals are likely to use data processing techniques similar to conventional data analysis.
Conclusion: Should You Learn Data Analysis?
Data Analysis is a data-handling process that aims to draw insights from otherwise meaningless data. Data analysis empowers businesses to base their decisions on their past records, as well as predict how well their decisions will turn out in the future.
Data Analysis is useful no matter what kind of business you are involved in. The use of data analysis ensures that you are making the best possible use of data, and are not making uninformed decisions. These decisions can wreak havoc on your business model if not planned carefully.
With ever-growing salaries, strong career growth projections, and a comparatively easy learning curve, Data Analysis holds the potential to add a lot of value to your data-centric career.