Data analysis is a growing field that will only become more and more relevant in the coming years. As the world becomes increasingly digitized, larger components of society will start to take place online. This means that the volume of information available online will increase, and the sheer amount of data to be analyzed will grow exponentially. This, in turn, means that new technologies and innovations can be pioneered using this data, which then furthers the cycle.
The key takeaway from all of this is that data analysts are going to have an abundance of employment opportunities in the next decade and beyond. Every company, charity, and government agency can benefit from expanding and developing their data analysis methods to maximize efficiency and boost productivity. Organizations that fail to keep up with this trend will get left behind, which is why they will rely on qualified analysts to give data-based recommendations for nearly every decision.
“We live in a world where nearly everything is logged, tracked, recorded, and stored. People who fully understand this, and understand how to capitalize on it, hold the keys to the future,” says Sergiy Kyrychenko, the CEO of Umnikey, LLC. His company has spent the last decade building a diverse portfolio of consumer review websites, aiming to help customers in a wide variety of industries find the best product or service for their needs. Umnikey, LLC’s success is built on the data analysis work that they do. Sergiy’s data analyst team provides objective examinations of subjective opinions, considering every relevant aspect of any dataset before them.
With these facts in mind, it is easy to see why data analysis is only going to get more and more important from here on out. As a result, many people of all ages today are looking to improve their data analysis abilities, given that the professional benefits of such a skill set are apparent. However, like with any booming industry, there is bound to be some competition as more people try to get in on the action. The question of employability and how to distinguish oneself in the job application process is hugely important.
While many data analysts are employed by a larger company or organization, other individuals may use data analysis for their own benefit, such as improving their small business. Data can be analyzed on both large and small scales, so it makes sense that data analysis is not limited only to the largest corporations and government agencies. Additionally, many people benefit from data analysis skills in their personal lives. Even a few basic analytical techniques can help somebody manage their finances, develop an exercise regimen, overcome an addiction, or track a hobby.
In short, virtually everybody can benefit from becoming better at analyzing data and information. Whether you’re looking for a total career switch or simply trying to add more structure and organization to your life, data analysis is a great talent to have. However, this field often carries a difficult learning curve and it is easy to get stuck and feel like you will never be able to make sense of vast arrays of numbers.
Aspiring data analysts would do well to follow these key pieces of advice:
- Know the tools of the trade: become more familiar with softwares that can process vast amounts of data. Google Sheets and Microsoft Excel are a good place to start, but there is far more that the world of data analysis has to offer. Professional data analysts often branch into computer science by using SQL, R, and Python for analysis and using Power BI and Tableau for visualization. Don’t be afraid if that sounds overwhelming: Sheets and Excel are still a budding data analyst’s best friend. As you progress, you will learn which tools are best suited for your specific niche or field.
- Take the chance to explore: once you have the technology you need, spend time experimenting with different functions that your analytics tools have to offer. Take advantage of the myriad of free resources available online. If applying for a data analysis job, gain an edge over the competition by mastering lesser-known tools and commands that can significantly increase your productivity.
- Be creative: find new ways to analyze the data. A good analyst correctly executes the required calculations and spits out the bottom-line number that they or their client wanted to hear. A great analyst goes outside the box and looks at the data in a different way, identifying parameters and calculating statistics that they or their boss never even knew they needed. Think about which aspects of the data may have been overlooked by the current analyses.
- Consider the context: remember that data is not just meaningless numbers in a void. Data is derived from the real world, and every dataset carries unique nuances and irregularities that are specific to its context. Investigate and thoughtfully consider what factors can make this dataset different from any other list of numbers. Don’t let yourself miss the forest for the trees; try to take a step back and look at the bigger picture.
Incorporating these strategies and mental frameworks into your daily work will help make you a stronger and more purposeful data analyst. Data analysis isn’t going to go away anytime soon—indeed, it will only become more important as digital technology becomes more present in everyday life. Through diligent work and perseverance, anybody can quickly master the art and science of data analysis.