Sign in or start a free trial to avail of this feature.
1. How Data Affects Businesses
Data literacy is the key skill of working with data. It’s becoming increasingly important because data is increasingly affecting modern businesses. Learn how this is happening in this lesson.
To explore more Kubicle data literacy subjects, please refer to our full library.
Lesson Goal (00:10)
The goal of this lesson is to learn about data’s growing impact on business.
What is Data Literacy (00:39)
Data literacy is the ability to read, work with, analyze, and argue with data. If you have data literacy skills, you’ll be able to ask questions of data, build knowledge, make decisions, and communicate meaning to others. The impact of data on business activities can be divided into two groups: activities that can be done faster with data, and new activities that can only be done using data.
Doing Things Faster With Data (01:19)
Many business activities can be greatly accelerated using data. An example of this is recruitment. Job applicants can record themselves answering questions on video, and these responses can be analyzed automatically by computer applications. This allows companies to screen far more applicants than they would without data and analytics.
Companies can also use online aptitude tests to gather information on a variety of skills that would be difficult to capture in a traditional interview. This allows companies to identify a wider range of characteristics than they would have been able to previously.
Doing New Things With Data (02:40)
Data also allows companies to do things they would never have been able to do previously. An example of this would be how companies in the financial sector identify fraud. For example, companies can analyze large amounts of transaction data in real time to identify possible fraudulent activity, or they can combine multiple different sources of information to identify possible inconsistencies that might indicate fraud is taking place.
Hi, and welcome to Kubicle's Introduction to Data Literacy. In this short course, we're going to explore why data analytics is increasingly important to businesses in this rapidly changing world, and how you can exploit tools and technology to adapt to this change. By taking this course, you'll gain an understanding of today's challenges, and learn important steps you can take to stay ahead of the curve. In this first lesson, we'll learn how data increasingly impacts modern businesses.
First, let's understand what data literacy is. Data literacy is the ability to read, work with, analyze, and argue with data.
Data literacy enables you to ask questions of data, build knowledge, make decisions, and communicate meaning to others. The growth of data collection and analysis means that data literacy is a key skill for anyone working in any sector.
The impact of data on business activities can be divided into two main groups, activities made faster using data, and activities made possible using data. Let's look at each of these individually.
Let's consider the example of recruitment. Without access to analytics, recruiting a new employee would involve manually scanning a large number of resumes, and then holding a series of in-person interviews.
With access to data analytics, video interview applications now allow job applicants to record themselves answering interview questions. A machine can then analyze the responses, considering factors such as words spoken, and determine if the applicant meets the company's standards. This may sound a bit dystopian, but a company using such a system can screen a higher volume of applicants far more quickly than traditional methods, theoretically, leading to better outcomes.
Analytics also allows companies to gather more information on applicants than would be possible in a conventional interview. For example, online aptitude tests are available that test for a wide variety of skills and aptitudes, such as decision-making, memory, emotional intelligence, and risk tolerance. The applications analyze responses given by applicants and judge the applicants' suitability for the role automatically. It would be possible to test for these skills without access to analytics software, but it would be a much longer and much more difficult process.
The second category of business activity affected by data includes activities that would be impossible without the ability to analyze data quickly and efficiently. An example of this is fraud identification in the financial industry. One method of identifying fraud is to find unusual patterns in bank account transactions.
For example, if a person has multiple transactions in different locations at the same time, then some sort of fraud is probably occurring. This sort of fraud could only be identified in real time using data analytics. A more manual process would only identify this type of fraud long after it had occurred.
Another method you use to identify financial fraud is to combine multiple different sources of data to detect inconsistencies. Many sources are available to a financial institution that would not have been available in the past, such as social media records. For example, if a car insurance company receives a claim for a crashed car from a customer, who is at the same time posting about being on vacation in another country on social media, then it is likely that some sort of fraud is occurring. Without the ability to access and analyze multiple sources of data, the insurance company would have no way of knowing this.
Data and analytics have the capability to transform pretty much any business, any sector, and any activity. Developing your own data literacy abilities is key to being able to participate in, and benefit from this transformation. Data is increasingly becoming a global language of business, and speaking that language will become a key aspect of most people's jobs.
This concludes our Introduction to Data in Business. In the next lesson, we'll learn about the most important analytic skills that you need to understand to be data literate.