Data analytics is a technology field that helps individuals and organizations make sense of the data that analysts collect, organize, and analyze. This career requires technical expertise to analyze and visualize data to help improve company decision-making and performance.<\/p>\n\n\n\n
Want to learn more about data analytics and how to work in this growing field? This guide has it all.<\/p>\n\n\n\n
In its simplest form, data analytics involves looking at data to find answers to specific questions. Businesses use data analytics to help them figure out how to optimize their productivity, processes, performance, and profits.<\/p>\n\n\n\n
\u201cData analytics involves preparing, cleansing, analyzing, and presenting data \u2014 it could be big data, streaming data, little\/high variety data, etc. \u2014 in a way that answers the \u2018big\u2019 or \u2018key\u2019 questions asked by business stakeholders,\u201d says Chris Mattmann, chief technology and innovation officer at NASA Jet Propulsion Laboratory and an adjunct research professor who teaches data science<\/a> and big data at the University of Southern California.<\/p>\n\n\n\n So, what is big data analytics? The key difference is that data analytics primarily involves structured (quantitative) data, while big data analytics may use raw and unstructured (qualitative) data. This makes big data both larger and more complex to analyze.<\/p>\n\n\n\n\t Enhance your data analytics skills in this free course from Quantium. Analyze a customer's dataset, make recommendations, and test your theories. <\/p>\n\t\t\t\t\n\t\t\t\t\t\t\t\t\t \n\t\t\t\t\t\tAvg. Time:<\/span>\n\t\t\t\t\t\t4-5 hours\t\t\t\t\t<\/p>\n\t\t\t\t\n\t\t\t\t\t\t\t\t\t \n\t\t\t\t\t\tSkills you’ll build:<\/span>\n\t\t\t\t\t\tData visualization, data validation, data wrangling, programming, statical testing, data analysis, commercial thinking\t\t\t\t\t<\/p>\n\t\t\t\t\n\t\t\t\t\t\t\t\t\t A career in data analytics can create a pathway into many different industries. In fact, virtually any<\/em> business, industry, or organization with data can benefit from leveraging data analytics to understand how to optimize its business. Data analysts<\/a> have become increasingly valued across diverse industries, as they play a vital role in driving organizational change.<\/p>\n\n\n\n \u201cSkills like those developed by data analysts are highly sought after in all industries,\u201d says Theresa Kushner, head of the North American Innovation Center at NTT Data Services, who has more than 25 years of experience in data analytics. \u201cAs more and more organizations turn to data analytics and data science to change the way they operate and help them grow and thrive, data analysts are entering the folds of every industry, from finance to healthcare, government to manufacturing, education to entertainment \u2014 and collaborating across departments like marketing, finance, and HR.\u201d <\/p>\n\n\n\n Aswini Thota, a lead data scientist at Bose Corporation with over 12 years of experience in data analytics, agrees that the need for data analysts is ubiquitous. \u201cData analysts are not just limited to tech or product companies,\u201d Thota says. \u201cIn fact, any medium to the large-scale company that uses enterprise resource planning systems to organize their operations hires data analysts.\u201d<\/p>\n\n\n\n Not every organization aligns data analysts in the same way, however. According to Thota, some businesses place all of their data teams under one center of excellence. Others prefer to organize by business functions, such as having a business analyst<\/a> forecast budgets or solve larger business problems.<\/p>\n\n\n\n >>MORE: <\/strong>Business Analyst vs. Data Analyst: What’s the Difference?<\/a><\/p>\n\n\n\n Some industries that use data analytics include:<\/p>\n\n\n\n The Bureau of Labor Statistics<\/a> reports that between 2022 and 2032, employment growth for operations research analysts, a job category that includes data analysts, should increase by 23%, emphasizing the high demand for these professionals. But how do you get started? A combination of education, training, and skills development can help you break into the field.<\/p>\n\n\n\n\t Experience what it's like working in data analytics in this free course from Tata. Discover how to anticipate business questions, decide what data visualization is best, then create reports for company leaders.<\/p>\n\t\t\t\t\n\t\t\t\t\t\t\t\t\t \n\t\t\t\t\t\tAvg. Time:<\/span>\n\t\t\t\t\t\t3-4 hours\t\t\t\t\t<\/p>\n\t\t\t\t\n\t\t\t\t\t\t\t\t\t \n\t\t\t\t\t\tSkills you’ll build:<\/span>\n\t\t\t\t\t\tData interpretation, data analysis, charts and graphs, data cleanup, dashboards\t\t\t\t\t<\/p>\n\t\t\t\t\n\t\t\t\t\t\t\t\t\t Graduating with a degree in a quantitative<\/a> area or STEM (science, technology, engineering, or math) is the most straightforward way to get into data analytics. A bachelor\u2019s degree in computer science, business analytics, mathematics, economics<\/a>, or statistics will enable you to learn core technical skills, such as SQL<\/a>, Python, statistics, and business intelligence.<\/p>\n\n\n\n However, you don\u2019t need a Ph.D. in data science or even a related bachelor\u2019s degree to become a data analyst \u2014 though these certainly can help. As an alternative to formal schooling, you can build your foundational knowledge to gain these skills in a more hands-on and experiential setting through online bootcamps, certifications, virtual job simulations, courses, or internships. <\/p>\n\n\n\n >>MORE:<\/strong> Best Coding Bootcamps Online for 2023<\/a><\/p>\n\n\n\n For example, conducting data analysis using real data and open-source code can prepare you for a career in data analytics. \u201cHave real examples that you\u2019ve solved and questions answered,\u201d Mattmann says. \u201cNot the solve-in-a-day ones \u2014 instead use the ones that take four to six weeks and have some \u2018meat\u2019 that you can show the results of to a hiring manager or recruiter<\/a>.\u201d <\/p>\n\n\n\n Along with building your technical chops, you should also expand your soft skills<\/a>. Kushner lists critical thinking<\/a>, curiosity, and creativity<\/a> as important soft skills that can complement your technical skills to offer more advanced and unique insight into data analytics. <\/p>\n\n\n\n Prospective data analysts should also develop a online portfolio<\/a> of their work to demonstrate their competence and passion in the field. Being inquisitive and asking questions about confidence in data can also help you land a job in data analytics. \u201cA lot of debate majors are great future analysts and data scientists<\/a>,\u201d Mattmann says.<\/p>\n\n\n\n >>Build practical skills:<\/strong> The Best Data Job Simulations on Forage to Jumpstart Your Career<\/a><\/p>\n\n\n\n Networking<\/a> is another powerful tool that can facilitate landing a job in data analytics \u2014 for example, through LinkedIn<\/a>. \u201cTalk about your work, your GitHub, your posts,\u201d Mattmann says. \u201cShow real examples of datasets and problems you\u2019ve solved. Get involved in the open-source community and different projects. Do tutorials in machine learning<\/a> and data science. Get certifications online. This is extremely valuable \u2014 sometimes as valuable as a four-year degree.\u201d<\/p>\n\n\n\n Kushner agrees that you should start building contacts in the fields you\u2019d like to work in so you have a chance at landing an entry-level position, at the very least. From there, you can work your way up. <\/p>\n\n\n\n Why choose data analytics as a career path? As with any field, it\u2019s essential to be aware of the potential positives and negatives of working in data analytics. Here are some of the key pros and cons, according to industry experts.<\/p>\n\n\n\n If you enjoy solving puzzles and interesting challenges, then data analytics may be an excellent fit for you. This career involves constantly looking at problems, analyzing the data, and identifying solutions, which can be especially rewarding when the business takes recommendations from the data analytics team seriously and acts upon them efficiently. \u201cSeeing an analysis accepted by the business and put into action is the greatest reward a data analyst can receive,\u201d Kushner says. <\/p>\n\n\n\n Also, because data is at the epicenter of innovation for most enterprises, that makes data analysts who can tame and decipher big data crucial members of any organization. \u201cData analysts play a vital role in the decision-making<\/a> process within companies and organizations,\u201d Thota notes. \u201cBusiness leaders use the insights and information gleaned from this data to make strategic investments, target customers, assess risks, and allocate capital.\u201d<\/p>\n\n\n\n In many instances, the insights from data analysis can directly impact employees\u2019 lives and the company\u2019s bottom line. You might need to mine for insights on critical questions such as:<\/p>\n\n\n\n \u201cThe realization that your insights informed your company\u2019s critical decisions can give you immense professional satisfaction,\u201d Thota says.<\/p>\n\n\n\n People who like having their work spotlighted may enjoy this career. Data analysts often need to present their findings to executives and other high-level decision-makers and build highly scalable systems. Both of these responsibilities increase the visibility of the data analyst\u2019s role. <\/p>\n\n\n\n \u201cData analysts inform all aspects of the business, from identifying potential customers and designing marketing campaigns to improving customer satisfaction,\u201d Thota explains. \u201cBusiness leaders and executives are increasingly interested in data and its potential to drive business growth.\u201d <\/p>\n\n\n\n In addition to making presentations<\/a> to leaders, data analysts are also responsible for enterprise-wide business intelligence systems. \u201cOnce a solution is finalized, data analysts leverage business intelligence tools to develop visualizations and reports that can provide a point-in-time view of a business function or an initiative,\u201d Thota says. \u201cThe systems that data analysts build are often deemed as the single source of truth and are used by many business users across the enterprise.\u201d <\/p>\n\n\n\n Working in data analytics is cross-functional by nature since these professionals need proficiency with many tools, such as programming languages, databases, data visualization, cloud computing, and statistics. <\/p>\n\n\n\n To work effectively, data analytics professionals possess a wide range of practical skills that are in high demand. And because the skills are easily transferable<\/a> from industry to industry, data analysts have impressive career mobility. <\/p>\n\n\n\n \u201cData analysts develop strong domain knowledge as they are expected to have a deep understanding of business operations and internal processes,\u201d Thota says. \u201cThis business acumen is highly desired in different roles such as management consulting<\/a>, business development, marketing, etc.\u201d<\/p>\n\n\n\n Mattmann points out that it can be very difficult in data analytics to collect \u201cground truth\u201d or know what \u201cdone\u201d means. \u201cSome industries are constantly in exploratory analysis mode, but never in product mode,\u201d Mattmann explains. \u201cSo you can feel stuck in the research world, and not the delivering world.\u201d<\/p>\n\n\n\n A possible drawback of working in data analytics is as simple as businesses ignoring recommendations and never seeing the value they can provide, explains Kushner. \u201cFor some data analysts, being stuck in a never-ending analytics loop signals \u2018analysis paralysis,\u2019 which is basically like death to a good data analyst,\u201d she says.<\/p>\n\n\n\n Since data analysts must balance technical expertise and business acumen, they need to possess a deep understanding of the business they\u2019re supporting and the technical tools and methods used to collect and analyze data. This means thinking on your feet and shifting gears quickly and flexibly as required. <\/p>\n\n\n\n \u201cWhile understanding new business and the corresponding systems can be fun at first, the need for constant learning and staying on top of the procedural changes in an organization can be a little intimidating,\u201d Thota says.<\/p>\n\n\n\n Most organizations operate in a constantly changing environment and must make tactical decisions to respond to evolving market conditions. As a result, it\u2019s typical in data analytics careers to find yourself managing \u201cfire drills,\u201d according to Thota. \u201cTo make these tactical decisions, leaders often rely on data analysts to provide them with rapid insights,\u201d he says. \u201cThis could lead to a high workload and tight deadlines for data analysts.\u201d Interested in exploring other data careers? Learn about the data engineering<\/a> field and what it takes to become a data engineer<\/a>.<\/p>\n\n\n\n Is data analytics your path? What analytical jobs are right for you? Take this quiz to find out. It’s completely free \u2014 you’ll just need to sign up to get your results!<\/p>\n\n\nData Analytics<\/h2>\n\t\t\t\t\t\t\t\t\t<\/div>\n\n\t\t\t\t\t\t\t\t\t
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What Analytical Jobs Are Right for Me? Quiz<\/h2>\n\n\n\n