Data Analyst vs. Data Scientist

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Data Analyst vs. Data Scientist

In our modern business world, a company leader who fails to tap into the potential of big data is like flying an airplane with a blindfold on. Big data can help you understand market trends, consumer behavior, measure KPIs, and target inefficient processes. As a whole, big data can serve as a guide when making important business decisions. When the world of business seems chaotic and unpredictable, big data is the leveraging force to help you make sense of it all. Read on to learn about Data Analyst vs. Data Scientist.

But all this doesn’t mean it’s easy to tap into the power of big data. Business leaders need the right tools and personnel to make sense of big data by “cleaning” it into accessible and understandable sets. Two positions in particular, data analysts and data scientists, are essential for businesses today to put big data to use for you and your company. 

In this blog, we’re taking a closer look at big data and how two key positions, data analysts and data scientists, use this tool to help businesses make smarter decisions. We also compare these two roles, investigating what a data analyst and a data scientist have in common and how they each offer unique contributions to the growth and effectiveness of a business. 

At Fully Accountable, we’re dedicated to serving the financial needs of ecommerce and tech companies across the United States and Canada. No matter your industry, our digital accountants and fractional CFOs will surpass basic bookkeeping tasks and help you uncover insight to increase the growth of your business. We have the tools and experience to help you take advantage of big data to make the right business decisions. 

WHAT IS BIG DATA?

We’ve all heard this term thrown around, but do you really have a clear idea of what it means? According to Oracle, big data can be defined as “data that contains greater variety, arriving in increasing volumes and with more velocity.” Essentially, big data is large, more complex sets of data that require new methods and tools for managing and making sense of this valuable information.

While big data provides new opportunities for insight into your business and industry, it also comes with inherent challenges, such as being able to store, organize, and then decode such large amounts of information. This is where data experts, including data analysts and data scientists, become essential. 

THE THREE V’S OF BIG DATA AND DATA ANALYTICS

When you’re talking about big data and data analytics, there are the three V’s you should always keep in mind: volume, velocity, and variety.

Whether you’re an accounting company or any other information-driven field, here’s a breakdown of the important factors of big data you should know:  

1. Volume: this refers to the sheer amount of data, which may be structured or unstructured, depending on the source. Some organizations can reach a volume of hundreds of petabytes of data.

2. Velocity: this refers to the rate at which your data is received and processed. High velocity data can function in real-time, which requires prompt evaluation and action on the part of your data analysts.

3. Variety: this refers to the different types of data your business can access. Traditional data often came in just one or two types, and thus, was much easier to organize in a relational database. However, now that there are so many unique types of data, including video and audio files, structuring big data has become a much greater challenge. 

WHY YOU NEED DATA ANALYSTS AND DATA SCIENTISTS

Big data can prove invaluable for your business. But is it all just about how much data you have? While more data is certainly valuable, what matters most is how you use your data. With effective data analysis, you can unlock key insights into your business and the market, allowing you to make improvements for nearly any aspect of your operations.

As your business grows, the complexity of your processes and operations inherently increases. To effectively scale your business, data can offer insight into the complexity, revealing patterns and trends. By understanding these patterns and trends, you can make more informed decisions for your business.

Big data can help you determine the size of a market opportunity, assess the value of certain products, utilize consumer insights, and measure the performance of your content and products. If knowledge is power, big data is about as powerful as it gets. 

WHAT IS A DATA ANALYST?

Data analysts are becoming an increasingly common position found in companies across a wide range of industries and fields. But what exactly does this position entail? According to Rasmussen University, a data analyst is someone who will “retrieve and gather data, organize it, and use it to reach meaningful conclusions.” From healthcare organizations to restaurant chains, data analysts can provide valuable insight into the operations of a company and help managers make effective, informed decisions.

Here are some of the core responsibilities of a data analyst:

·  Conduct data research.

·  Write SQL queries to extract data.

·  Clean and organize data into manageable sets.

·  Express data via visual representations, such as charts and graphs.

·  Perform quantitative analysis.

·  Contribute to KPI reporting via data analytics. 

WHAT IS A DATA SCIENTIST?

In many ways, a data scientist takes a more macro approach to data analytics. While data analysts often focus on very specific questions and solutions, a data scientist takes a broader look at how data affects the business and informs company decisions. Data scientists often have a background in mathematics and generally spend more time developing tools and methods for extracting and analyzing data. In many cases, data scientists develop the tools used by data analysts to run queries, extract information, and clean data sets.

Here are some of the core responsibilities of a data scientists:

·  Mine and analyze data from databases.

·  Assess the accuracy and usefulness of data sources and data-gathering techniques.

·  Create data models and algorithms.

·  Coordinate with multiple teams and developers to implement data tools.

·  Use predictive modeling to improve company processes.

·  Design processes and data tools to monitor and analyze KPIs.

It’s important to note that each business will define “data analyst” and “data scientist” in slightly different terms. As a result, the specific responsibilities of these positions can be fluid and different depending on the industry and company’s needs. If you’re pursuing work as either a data analyst or data scientist, be sure to carefully review the specific qualifications and responsibilities that will be included in the job posting. 

CONCLUSION – DATA ANALYST VS DATA SCIENTIST

In recent years, big data has increasingly become a powerful tool. Regardless of your industry or professional field, big data provides insight into market trends, consumer behavior, and your own business processes to help you make the right decisions. By working with experienced data professionals, such as data analysts and data scientists, you can tap into the power of big data and gain control over the future of your business. 

At Fully Accountable, we’re here to help your business grow—no matter your industry or the size of your workforce. With our professionalism, advanced tools and data, and years of experience, we can help your business have its best fiscal year to date. 

Contact us to learn more about big data and how outsourced accounting and a fractional CFO can benefit your business—no matter the size or industry. Together, let’s change your business for the better. 

Heidi Cake

Heidi Cake

Author at Fully Accountable | 1-877-330-9401 | www.fullyaccountable.com

Heidi Cake is our Data Director. She studied at Indiana Wesleyan University with a degree in BS Strategic Communications and BS Leadership Studies and specializes in analyzing anything in her path and creating aesthetic appeal to visual documents. Heidi spent the first few years after college working in the non-profit sector on teams where she was handed anything that needed to be communicated creatively. She realized her most loved being able to communicate complex, abstract ideas which made her return to her love of numbers and data. Heidi brings an equally creative and analytical mind to the task of analyzing and communicating client data and statistics.