Categories

Data Science and Analysis

Data Science and Analysis

Unlock the power of data to drive business decision-making, and gain in-demand skills in data science and analysis through online short courses tailored for technical and non-technical professionals, as well as business leaders.

Register for a data science or analysis course

The volume of data businesses generate daily is increasing year on year.1 This vast amount of data needs to be quantified and analyzed if businesses hope to gain value from it.

As a result, there’s a global demand for people with data skills. The Bureau of Labor Statistics (BLS) shows that the demand for professionals like data scientists and data analysts is growing much faster than any other occupation, with a projected growth of 16 percent by 2028.2

Organizations are responding to this widening skills gap by either upskilling existing employees through data science and data analytics courses or by recruiting those who already have data science and data analysis skills.3

No matter your data capabilities, GetSmarter has a broad range of online data science and analysis courses, spanning from entry-level data analysis and visualization courses to more technical data science courses covering coding and in-demand tools. These courses are ideal for data-driven professionals who want to improve their data analysis and visualization skills in order to provide actionable insights for their organization. Those in non-technical, decision-making roles will also find suitable courses to strengthen the data science capabilities of their organization and improve business intelligence.


What is data analysis and data science?

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

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

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.


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.


As data scientists and data 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

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 data analysts analyze, 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 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:23

  • 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 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.24 Storytelling is also an effective presentation skill that frames data insights in a way that tells a meaningful story25
  • Technical skills and tools. The capacity to use software programs such as SQL and Python, which, according to LinkedIn, are the most commonly used data query and programming languages.23 Others include XML, Javascript, R, SAS, Hadoop, and machine learning applications

Whether your background is technical or not, learning data science or data analysis in one of GetSmarter’s online short 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? Online short courses in data science, 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.


1(Feb, 2018). ‘Data analyst, the most in-demand job of the coming years’. Retrieved from Morning Future.
2(Sep, 2019). ‘Computer and information research scientists’. Retrieved from Bureau of Labor Statistics.
3Gaskell, A. (Jun, 2018). ‘Organizations striving to close the data science skills gap’. Retrieved from Forbes.
4(Nd). ‘What is data science?’. Retrieved from Data Jobs.
5(Feb, 2018). ‘Data analyst, the most in-demand job of the coming years’. Retrieved from Morning Future.
6(Nd). ‘What is data science?’. Retrieved from Data Jobs. Accessed April 23, 2020.
7(Nd). ‘What is data science?’. Retrieved from Oracle. Accessed April 23, 2020.
8Fedak, V. (May, 2018). ‘Big data analytics in the banking sector’. Retrieved from Medium.
9Krivaa, K. (2019). ‘The value of real-time data analysis for different sectors’. Retrieved from ReadItQuick.
10Lebied, M. (Jul, 2018). ‘12 examples of big data analytics in healthcare that can save people’. Retrieved from DataPine.
11Krawitz, M. Et al. (Aug, 2018). ‘How higher-education institutions can transform themselves using advanced analytics’. Retrieved from McKinsey.
12Kazemi, Y. (Jan, 2019). ‘AI, big data and advanced analytics in the supply chain’. Retrieved from Forbes.
13Krivaa, K. (2019). ‘The value of real-time data analysis for different sectors’. Retrieved from ReadItQuick.
14Krivaa, K. (2019). ‘The value of real-time data analysis for different sectors’. Retrieved from ReadItQuick.
15Krivaa, K. (2019). ‘The value of real-time data analysis for different sectors’. Retrieved from ReadItQuick.
16McLlaughlin, M. (Dec, 2018). ‘How data analytics is revolutionizing sports’. Retrieved from BizTech Magazine.
17Durcevic, S. (Nov, 2019). ‘Top 10 analytics and business intelligence trends for 2020’. Retrieved from Datapine.
18Kervizic, J. (Feb, 2020). ‘Data science career path and progression’. Retrieved from Medium.
19(Jul, 2019). ‘Data science in the new economy’. Retrieved from the World Economic Forum.
20Ying, J. (Dec, 2019). ‘How we mapped the ‘skills genome’ of emerging jobs’. Retrieved from LinkedIn Engineering.
21Sigelman, M. Et al. (Jan, 2019). ‘The hybrid job economy’. Retrieved from Burning Glass Technologies.
22Sigelman, M. Et al. (Jan, 2019). ‘The hybrid job economy’. Retrieved from Burning Glass Technologies.
23(Nd). ‘How to become a data analyst – complete career guide’. Retrieved from Discover Data Science. Accessed April 23, 2020.
24(Jun, 2019). ‘Salesforce and Tableau: a merger of hybrid skills’. Retrieved from Burning Glass Technologies.
25Diamada, A. (Jun, 2019). ‘Storytelling in data science’. Retrieved from PWC.
26Ying, J. (Dec, 2019). ‘How we mapped the ‘skills genome’ of emerging jobs’. Retrieved from LinkedIn Engineering.


Register for a data science or analysis course

The volume of data businesses generate daily is increasing year on year.1 This vast amount of data needs to be quantified and analyzed if businesses hope to gain value from it.

As a result, there’s a global demand for people with data skills. The Bureau of Labor Statistics (BLS) shows that the demand for professionals like data scientists and data analysts is growing much faster than any other occupation, with a projected growth of 16 percent by 2028.2

Organizations are responding to this widening skills gap by either upskilling existing employees through data science and data analytics courses or by recruiting those who already have data science and data analysis skills.3

No matter your data capabilities, GetSmarter has a broad range of online data science and analysis courses, spanning from entry-level data analysis and visualization courses to more technical data science courses covering coding and in-demand tools. These courses are ideal for data-driven professionals who want to improve their data analysis and visualization skills in order to provide actionable insights for their organization. Those in non-technical, decision-making roles will also find suitable courses to strengthen the data science capabilities of their organization and improve business intelligence.

What is data analysis and data science?

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

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

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.

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 data 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

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 data analysts analyze, 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

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:23

  • 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 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.24 Storytelling is also an effective presentation skill that frames data insights in a way that tells a meaningful story25
  • Technical skills and tools. The capacity to use software programs such as SQL and Python, which, according to LinkedIn, are the most commonly used data query and programming languages.23 Others include XML, Javascript, R, SAS, Hadoop, and machine learning applications

Whether your background is technical or not, learning data science or data analysis in one of GetSmarter’s online short 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? Online short courses in data science, 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

1(Feb, 2018). ‘Data analyst, the most in-demand job of the coming years’. Retrieved from Morning Future.
2(Sep, 2019). ‘Computer and information research scientists’. Retrieved from Bureau of Labor Statistics.
3Gaskell, A. (Jun, 2018). ‘Organizations striving to close the data science skills gap’. Retrieved from Forbes.
4(Nd). ‘What is data science?’. Retrieved from Data Jobs.
5(Feb, 2018). ‘Data analyst, the most in-demand job of the coming years’. Retrieved from Morning Future.
6(Nd). ‘What is data science?’. Retrieved from Data Jobs. Accessed April 23, 2020.
7(Nd). ‘What is data science?’. Retrieved from Oracle. Accessed April 23, 2020.
8Fedak, V. (May, 2018). ‘Big data analytics in the banking sector’. Retrieved from Medium.
9Krivaa, K. (2019). ‘The value of real-time data analysis for different sectors’. Retrieved from ReadItQuick.
10Lebied, M. (Jul, 2018). ‘12 examples of big data analytics in healthcare that can save people’. Retrieved from DataPine.
11Krawitz, M. Et al. (Aug, 2018). ‘How higher-education institutions can transform themselves using advanced analytics’. Retrieved from McKinsey.
12Kazemi, Y. (Jan, 2019). ‘AI, big data and advanced analytics in the supply chain’. Retrieved from Forbes.
13Krivaa, K. (2019). ‘The value of real-time data analysis for different sectors’. Retrieved from ReadItQuick.
14Krivaa, K. (2019). ‘The value of real-time data analysis for different sectors’. Retrieved from ReadItQuick.
15Krivaa, K. (2019). ‘The value of real-time data analysis for different sectors’. Retrieved from ReadItQuick.
16McLlaughlin, M. (Dec, 2018). ‘How data analytics is revolutionizing sports’. Retrieved from BizTech Magazine.
17Durcevic, S. (Nov, 2019). ‘Top 10 analytics and business intelligence trends for 2020’. Retrieved from Datapine.
18Kervizic, J. (Feb, 2020). ‘Data science career path and progression’. Retrieved from Medium.
19(Jul, 2019). ‘Data science in the new economy’. Retrieved from the World Economic Forum.
20Ying, J. (Dec, 2019). ‘How we mapped the ‘skills genome’ of emerging jobs’. Retrieved from LinkedIn Engineering.
21Sigelman, M. Et al. (Jan, 2019). ‘The hybrid job economy’. Retrieved from Burning Glass Technologies.
22Sigelman, M. Et al. (Jan, 2019). ‘The hybrid job economy’. Retrieved from Burning Glass Technologies.
23(Nd). ‘How to become a data analyst – complete career guide’. Retrieved from Discover Data Science. Accessed April 23, 2020.
24(Jun, 2019). ‘Salesforce and Tableau: a merger of hybrid skills’. Retrieved from Burning Glass Technologies.
25Diamada, A. (Jun, 2019). ‘Storytelling in data science’. Retrieved from PWC.
26Ying, J. (Dec, 2019). ‘How we mapped the ‘skills genome’ of emerging jobs’. Retrieved from LinkedIn Engineering.

Why choose GetSmarter?

Read about our approach to course selection, design and delivery.

Learn More