Daily Tasks of a Data Analyst

What is Data Analytics?

Data analytics is the set of techniques used to analyze raw data (unprocessed data) in order to extract relevant information, trends, and insights. This process includes collecting data, organizing it, and storing it, then performing statistical analysis on the data. Once the information is collected, conclusions can be drawn from it, which can be used for problem-solving, business processing, decision-making, and predictions that can inform what a company’s next steps should be. This process relies on disciplines like mathematics, statistics, and computer programming.

Growing Demand for Data Analysts

Data Analysts are in high demand as companies expand their analytic capabilities to keep up with the ever-growing stream of data that must be processed and analyzed. Cloud computing, along with mobile data traffic and AI technologies, is part of a rapid expansion not only of the volume of data that has to be stored and processed but also its complexity. In 2018, the Global Big Data Analytics Market was estimated to be worth $37 billion. This number is projected to reach $105 billion by 2027. Data Analysts and Data Scientists are playing a more important role than ever with big data, and likely will continue to do so in the coming years.

Daily Tasks of Data Analysts

Data Analysts are relied on in any industry that uses data, such as fast-food chains, retail stores, and healthcare providers. No matter the industry, most Data Analysts are tasked with finding insights in data that can be used to learn more about the needs of the end user or customer. Although the daily tasks of a Data Analyst depend on the kind of data they are handling, as well as the project at hand, nearly all Data Analysts are involved with data gathering, organizing, and analyzing.

Here are a few of the most common, and universal, tasks a Data Analyst will execute on a daily basis:

• Designing and maintaining databases: Data Analysts must ensure that databases are running smoothly, which involves fixing data-related problems and coding errors. The process of creating a database’s structure allows Data Analysts to model data based on such parameters as what data types should be collected or stored, as well as how the categories of data related to one another.
• Collecting data: Data is at the heart of a Data Analyst’s job, so collecting it plays an integral role in their daily work tasks. Data that is mined from primary and secondary sources must then be reorganized into a format that can be understood by a human or machine. Often, Data Analysts work with Web Developers to streamline the data-collection process. The more automated and reusable a routine for data collection is, the more streamlined the process becomes.
• Filtering and cleaning data: Raw data often has outliers, duplicates, or errors present that must be filtered out before the data can be processed. Cleaning data enables a Data Analyst to maintain data quality to ensure any interpretations of the data won’t be incorrect or skewed.
• Identifying patterns: Before a report can be generated, and data can be used to tell a story, a Data Analyst must locate valuable patterns within the data itself. Most Data Analysts report in regular time frames, like weekly or quarterly, to ensure that trends over time are noted.
• Using statistics to interpret data: Various statistical tools must be applied to datasets in order to interpret data, as well as isolate patterns and trends. Statistics plays a vital role in the Data Analyst’s job in that it helps to contextualize the work based on local, national, and international trends that have implications for the industry or company.
• Collaborating: The notion that a Data Analyst works in isolation, apart from the others at an organization, is largely a myth. Most Data Analysts regularly interact with those in various departments, such as salespeople, engineers, programmers, and marketers. They also typically collaborate with database developers and data architects. Because so much interdepartmental interaction occurs in a Data Analyst’s job, good communication skills are essential.
• Creating reports: A good portion of a Data Analyst’s time is devoted to creating reports for both those within an organization as well as clients. These reports provide key insights about areas for improvement, as well as emerging trends. A successful report involves much more than collecting numbers to display; it must weave together a clear, compelling narrative that can be accessed by decision-makers who aren’t trained as analysts.
• Documenting the analytic process: Document the process is an important act in that it helps stakeholders appreciate the steps that went into analyzing the data so that the findings can be duplicated.
• Presenting the findings: The final stage of the data analytics process involves sharing the findings with others within an organization or external stakeholders. Visualizations such as reports and charts are used to visually present the information in a way that’s accessible and engaging.

In most corporations, the job of a Data Analyst is growing more complex, as new modeling and prescriptive analytic techniques are becoming more mainstream for analysis. The integration of machine learning and AI provides Data Analysts with helpful ways to automate and streamline tasks, but also means that those working with big data must wear many hats to provide their company with the most meaningful insights from the data.

Hands-On Data Analytics Classes

The best way to learn about the current best practices, trends, and industry-standard software and tools in data analytics is to consider enrolling in one of Noble Desktop’s data analytics classes. Courses are offered in New York City, as well as in the live online format in topics like Python, Excel, and SQL.

In addition, more than 130 live online data analytics courses are also available from top providers. Topics offered include FinTech, Excel for Business, and Tableau, among others.

Courses range from three hours to six months and cost from $219 to $27,500.

Those who wish to study in an intensive educational environment may also consider enrolling in a data analytics or data science bootcamp. These rigorous courses are taught by industry experts and provide timely, small-class instruction. Over 90 bootcamp options are available for beginners, intermediate, and advanced students looking to master skills and topics like data analytics, data visualization, data science, and Python, among others. Noble’s Tableau Bootcamp provides interested learners with 12 hours of instruction on this powerful tool and how it can be used to create stunning data visualizations.

Are you searching for a data analytics class near you? If so, Noble’s Data Analytics Classes Near Me tool provides an easy way to locate and browse approximately 400 data analytics classes currently offered in in-person and live online formats. Course lengths vary from three hours to 36 weeks and cost $119-$27,500.