What is Data Analytics?
Data is everywhere; it comes in different sizes and from different sources. Each day, an estimated 2.5 quintillion bytes of data are created. The past two years alone accounted for 90% of this data creation. There’s data in each second of recorded security camera footage, every open-ended survey question response, and even in the quarterly grades of all the students in a given school district. However, until this data is sorted and analyzed, none of it is actionable. But what to do with it all? This is where data analytics comes in.
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 are useful 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.
This article will explore the important role data analytics and data science play in the Census.
Applying Data Analytics to the Census
Every ten years, the United States performs the Population and Housing Census. Its goal is to provide a count of the number of residents in the U.S., information that’s important to allot the number of seats each state has in the House of Representatives. The Census also helps lawmakers know how to decide which communities and states receive federal funds for such endeavors as building new schools and hospitals.
Data Scientists and Data Analysts are employed by the Census Bureau to help implement new technologies and data sources into its various programs. Here are some of the main ways the U.S. Census relies on the field of data analytics to collect, analyze, and visualize big data:
- The U.S. Census Bureau uses big data sources and various forms of technology to more efficiently analyze existing data, as well as to gather new insights into how the private sector is performing. Because the Census Bureau is situated within the Federal Statistical System, it can combine and generate new insights and statistical products. By applying cutting-edge techniques for statistical analysis, the U.S. Government is able to reduce costs while gathering accurate, up-to-date information. When partnered with other agencies within as well as beyond the federal government, the Census Bureau is able to:
- Reduce the cost of conducting surveys by incorporating predictive models to field and train representatives.
- Improve various aspects of healthcare.
- Indicate how research funding at various universities helps students secure careers, and helps local economies.
- Update the NAICS classification for every business in the country every year.
- Every five years, the U.S. also conducts the Economic Census, which allows the government to apply data science measures to how the economy and business sector is progressing, and to implement business and economic decisions based on this information.
- The commercial sector also benefits from the Census. Small local retailers, as well as national corporations, utilize demographic data when considering where to expand or better reach their target market. In addition, the Census offers important information pertaining to the income level, and age, education level of a local population, information that can be particularly helpful for those deciding where to open a new store.
- The U.S. Government has also performed a Census of Government every five years since 1957, in the years that end with 2 and 7. It is performed to evaluate local, state, and federal fiscal relationships, as well as to offer benchmark figures representing public employment and finance. Both state and local governments rely on the data collected in the Census of Government to establish budgets, provide programs, and conduct comparative analyses.
- When predictive analytics is applied to Census data, it can provide valuable insights into homebuyers who may soon wish to sell their properties due to changes in their life circumstances.
- By incorporating machine learning methods and modeling techniques to data about the economy and population, it’s possible to classify and predict patterns that will emerge in the data. Machine learning makes it possible for the U.S. Government to extract meaningful insights from the huge volume of complex data it collects on the population. Computers are able to unearth hidden patterns within the data that would be overlooked by the human eye. Machine learning plays an important role in:
- Using satellite imagery to estimate population numbers.
- Classifying businesses into particular NAICS codes.
- Providing accurate estimations of survey response propensity in Census tracts or blocks.
- Data analytics provides a powerful tool for helping to illustrate the distribution of those in the U.S. who have particular health problems, such as vision or hearing loss. By applying machine learning capabilities to microdata collected from the U.S. Census, new patterns emerge that illustrate the lives of people in the country, block to block, and help to paint a comprehensive picture of their health, financial situation, and other demographic information.
- Segmentation is a powerful tool used by Data Analysts who manage Census data. It involves dividing the population into various subgroups. It provides insights into the distribution of these groups across the country. In addition to being helpful to the U.S. Government, this data is also useful to other stakeholders, such as sales teams, election campaigns, businesses wishing to expand, and nonprofit organizations, among others.
- Artificial intelligence (AI) algorithms can be incorporated to scan public social media posts to alert the U.S. Census Bureau about any potentially incorrect or inaccurate reports individuals made in their Census responses. AI makes it possible to pull billions of conversations, a number that would be impossible to process using humans. In addition, AI-enabled “Smart Alerts” notify the Bureau of posts in which disinformation is gaining too much of a following or response.
In the future, it is likely that the U.S. Census Bureau will continue to rely on techniques from data science and analytics, such as AI, machine learning, and segmentation, to offer even more accurate and affordable insights into the population.
Hands-On Data Analytics Classes
A great way to learn more about data analytics is to enroll 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 $60,229.
Those who are committed to learning 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.
For those searching for a data analytics class nearby, Noble’s Data Analytics Classes Near Me tool provides an easy way to locate and browse approximately 400 data analytics classes currently offered in the in-person and live online formats. Course lengths vary from three hours to 36 weeks and cost $119-$60,229.