Data Science and Analysis

What is data analysis?

Data analysis is the process of extracting valuable business information from data through statistical analysis.⁴ Analysts use technology and software to collect and evaluate data to identify patterns that are relevant to the business.⁵

What is data science?

Data science is an interdisciplinary field that gives organizations actionable business insights from complex data sets by utilizing scientific methods, processes, technical software tools, and programming languages, such as Python and R.⁶ Data science exposes trends and gives insights that business leaders can use to improve products and services, and optimize decision-making.⁷

Why learn data science online?

The real value of learning data science and data analysis is the ability to accurately translate big data into insights that can positively impact an organization’s performance. Gaining these skills is a worthwhile investment, as this skill set will continue to be in high demand as the need for accurately interpreted data gains importance with business decision-makers.

To become a data scientist or analyst, an online data science course offered by a world-class university can assist you in achieving this. While it can be difficult to determine which one is the best fit for you, GetSmarter offers a range of different data sciences courses from high-ranking institutions. To find the right data science certificate course, you should consider your goals and what you want to get out of the online learning experience.

What are the applications of data analysis and data science?

The uses of data science and analysis span every industry, with applications found in finance and insurance, media and marketing, healthcare, education, manufacturing, trade, transportation, sports, and energy.

Some uses and applications of data science and analytics in multiple sectors include:

• Banking and securities: to reduce fraudulent transactions⁸
• Communications and media: real-time, simultaneous reporting across several platforms⁹
• Healthcare: collecting public health reports and highlighting the global spread of viruses¹⁰
• Education: updating and upgrading prescribed literature¹¹
• Manufacturing: optimizing supply chain management¹²
• Insurance: handling claims through analytics and development of new products¹³
• Consumer trade: predicting and managing staff and stock needs¹⁴
• Transportation: improving traffic and logistics planning¹⁵
• Sports: monitoring team and individual player performance¹⁶

Coupled with the rising demand for people with data science and data analysis skills is an increasing need for managers and business leaders who understand the collaborative value data-skilled professionals can deliver.¹⁷ Business leaders who harness data science and data analysis abilities in their decision-making, and focus on recruiting and retaining the best data talent for their organization, will help drive growth and a competitive advantage.

Careers in data science

As data scientists and analysts are relatively new professions, they don't have clearly defined career paths. People with backgrounds ranging from computer sciences and engineering to economics and marketing are pursuing careers in this field.¹⁸

Data scientists and analysts

Those interested in careers in data science and data analysis will find themselves in a career segment that is experiencing an all-time high.¹⁹

For those looking to grow a career in data science, knowing how to use popular programming languages like Python is crucial for many data analytics roles. More than analyzing data, data scientists and analysts serve as interpreters of this data to business decision-makers who are not necessarily technically oriented. This is often done with visualization tools like Tableau.²⁰ Additionally, a career as a data analyst requires working knowledge of Microsoft Excel and SQL, as analysts analyze data, and interpret and evaluate data with these tools.

The rise of more complex, hybrid jobs requires that a growing number of professionals across business areas become comfortable working with analytics and data.²¹ Professionals who continue to upskill themselves in these hybrid roles typically enjoy greater job security, as the majority of hybrid jobs are immune to automation.²² Data science is one area of study that can help professionals build the skills necessary for hybrid roles. Data science is the process of extracting insights from data using scientific methods. This involves tasks such as data cleaning, data exploration, data modeling, data mining, data manipulation, and data visualization.²³

Machine learning

Machine learning is a branch of data science that deals with the development of computer programs that can learn from data without being explicitly programmed. Machine learning algorithms can automatically improve their performance as they are exposed to more data. This makes them well-suited for tasks such as predictive modeling and classification.²⁴ There are data science courses available at GetSmarter that teach both data science and machine learning. These online data science courses typically cover a range of topics, from data science projects, basic data cleaning and exploration to more advanced machine learning techniques.

Apart from machine learning, data science also involves the use of artificial intelligence (AI). AI is a field of computer science that deals with the development of intelligent agents, which are systems that can reason, learn, and act autonomously. AI has been used for many years in tasks such as game playing, natural language processing, and machine translation.²⁵

One of the most popular machine learning techniques is linear regression. Linear regression is a technique that allows you to predict the value of a variable based on the values of other variables. It’s a simple, yet powerful technique that can be used for data analysis and machine learning.²⁶

Skills required for a career in data science or data analysis

Data analysts typically have strong technical skills accompanied by in-depth industry knowledge. Here are the top skills needed to have a successful career as a data scientist or data analyst:²⁷

• Data analytics. The ability to evaluate large amounts of data in various formats to find conclusive insights
• Communication. Capabilities to translate complex ideas and data into coherent and understandable documents or reports. Soft skills are critical in delivering findings through clear communication to both technical and non-technical audiences
• Critical thinking. Formulate conclusions by carefully analyzing numbers, trends, and data
• Attention to detail. Draw accurate conclusions from meticulous analysis, interpretations, and evaluations of data sets
• Math skills. The faculty to process numerical data
• Data presentation and data visualization skills. There’s a clear rise in demand for people who can present data visually as a communication aid. Job postings seeking data visualization skills have grown by 540 percent in five years, with postings specifying the ability to use the data visualization tool Tableau, growing by a remarkable 1,165 percent.²⁸ Storytelling is also an effective presentation skill that frames data insights in a way that tells a meaningful story²⁹
• Technical skills and tools. The capacity to use software such as SQL and Python programming, which, according to LinkedIn, are the most commonly used data query and programming languages.²³ Others include XML, Javascript, R programming language, SAS, Hadoop, and machine learning applications
• In-depth understanding of machine learning algorithms and techniques. Machine learning is a scientific field that is focused on the development of computer programs that can learn from data, without being explicitly programmed. This involves the use of a variety of techniques, such as probability and statistics, to make predictions or decisions. Machine learning algorithms are used to create models that can help predict future events or to identify patterns in data³¹

Whether your background is technical or not, learning data science or data analysis in one of GetSmarter’s data science courses will help you develop in-demand skills to provide actionable business intelligence. GetSmarter’s flexible model offers fully supported learning and certificates from leading institutions around the world upon completion.

If you seek to improve your data interpretation, visualization, and communication skills by using Tableau, SQL, and VBA, data analysis and visualization courses will help expand your knowledge. Ready to advance your programming language proficiency? Data science courses, using Python, teach you how to apply data to a model for greater insight into business problems. Leaders looking to drive data-driven solutions could also benefit from a data science for business online course, which offers insights into deploying effective strategies.

Sources

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