A Day in the Life of a Data Analyst: What Do We Do Daily?
Have you ever wondered what a data analyst does in a day? and what are the skills required to be a data analyst?
In the age of data, a data analyst is one of the fastest growing and most highly demanding careers. Every activity we perform daily, whether buying, shopping, traveling, or internet surfing, are all recorded and inherit great value. Data is used by businesses as a resource to help them gain customer knowledge and design the strategies that hook them and eventually increase their sales and maximize their profits. A data analyst gathers and uncovers the power of data that leads to that success.
What is a data analyst?
A data analyst uses data to answer questions by retrieving and turning a tremendous amount of raw data into a ready-to-use format and then going through the data to uncover hidden patterns and trends to reach meaningful insights that answer business questions and guide informed decisions and strategic planning.
The core responsibilities of a data analyst at Sertis
At Sertis, we have three core responsibilities that describe how our data analysts work.
"We turn data into information
We transform information into insight
We use insight to reach business conclusions for informed and practical decision-making and planning."
A data analyst's daily tasks
A data analyst's daily tasks involve working and communicating with others, ranging from meeting with the team members, analyzing problems and setting a mutual goal with clients, to presenting a conclusion to stakeholders. This is why interpersonal skills and communication skills are necessary for being a data analyst.
A day of a data analyst often starts with retrieving data from the database, which we call primary data. This task may be the most technical aspect of a data analyst's job which requires the knowledge of programming languages, such as SQL, to perform data queries. Also, a data analyst needs an understanding of database infrastructure and automated data collection.
To clean data is to remove duplicates, errors, or outliers and resolve data inconsistencies and misplacements to prepare for accurate analysis.
The next step is to analyze the primary data with the secondary data, e.g., market research, operation performance, business performance, trends, and news in the industry to find the correlation and connection between data and provide a clear understanding of what data is telling us.
Then, a data analyst spot trends and patterns in data and reach meaningful insight that will either confirm the clients' presumptions or provide them with new knowledge they had not previously known. Insight is a key deliverable of a data analyst's job that we will hand over to clients to support their decision, transformation, or execution, add value, increase profit, accelerate growth, and improve competitiveness.
A data analyst presents conclusions and insight by generating reports in the forms of graphs and tables, or an automated dashboard. This is an aspect that requires a data analyst to have data visualization skills to translate data into visual elements that are easier to understand. A data analyst who masters data visualization is considered an exceptional data analyst.
Data analyst's key deliverables
A data analyst's key deliverables throughout the routines can be categorized into 2 types:
An insight report is to answer a specific question from clients, for example, if the client asks how much the sales decline in August is and what is the cause, a data analyst needs to find the answer and present it using easily-understood visualizations, such as graphs or tables.
An automated dashboard is a visual display of visualized data that is automatically updated every time data changes in real-time. Some data analysts are responsible for designing and building this dashboard to give clients real-time access to data such as sales, number of customers, number of visitors, or production performance. This dashboard is centralized with automated updates and accessible at any time.
The deliverable insight produced by a data analyst is beneficial for business in various ways, for example, a data analyst searches through purchasing records and consumer trends to predict which product customers would likely buy and present it to the right target group at the right time. Businesses are no longer needed to conduct market testing or find the right product through trials and errors because they are backed by data and statistics that will help them make informed decisions. The right product will eventually generate more sales and drive more profit.
Furthermore, a data analyst can analyze customer lifetime value with other factors to find what affects the increase and decline or the value, and find trends and patterns. This insight enables strategy and campaign design and product selection to maintain and boost the value. We can also predict customer churn by monitoring changes in value to find the cause and prevent the churn in time.
The strategies developed from the insight delivered by a data analyst will support a business' problem identifying and solving and informed and data-based strategic planning, which will reduce the misstep, boost sales, and maximize profit.
Must-have skills for a data analyst
The main skills required for a data analyst are represented in a form of Borromean rings-
programming languages, statistical skills, and business acumen.
It can be divided into hard skills and soft skills.
Having statistical skills
Having business acumen, market research, and key metrics
Knowing SQL, databases, and database infrastructure
Having an ability to use data analytics and visualization tools, e.g, Power BI, Tableau, and Excel
Having critical thinking and analyzing skill
Having visual story-telling skills
Having communication and collaboration skills
Be part of our team and grow together with other talented people into the new era of AI and data https://www.careers.sertiscorp.com/jobs