Understanding the Importance of Data: Why Data is Crucial for Business and Society
In today’s world, data has become the cornerstone of innovation and progress. We see it being used across industries, from healthcare to retail, and it’s become an essential component of our daily lives. But what exactly is data, and why is it so important? In this article, we’ll dive deeper into the world of data, exploring its different types, uses, and benefits.
In simple terms, data refers to a collection of facts or information, which can include numbers, words, measurements, observations, and more. It’s usually gathered through various means, such as sensors, surveys, or online forms. Once collected, the data is transformed into a format that computers can read and process. This process is called structuring, which turns data into machine-readable information.
Understanding Human-readable and Machine-readable Data
When we talk about data, we often refer to it in two forms: human-readable (or unstructured) and machine-readable (or structured). The former refers to information that humans can understand and interpret, such as a block of text or an image.
The latter is information that computers can read and process. Structured data is essential in business and computing because it allows us to automate tasks and generate insights that we couldn't do manually.
Different Types of Data
The world of data is vast and diverse, and we can categorize it in several ways. Here are four common types of data that we often come across:
This type of data includes any information that is specific to an individual, such as their demographics, location, or email address. Social media sites, online retailers, and other businesses often collect this data to create personalized experiences for their users. However, the misuse of personal data can also lead to privacy concerns and controversies.
Transactional data is information that is generated by an action, such as making a purchase, clicking on an ad, or visiting a web page. It's usually captured by businesses through various systems, such as Google Analytics or their internal data capture tools. Analyzing transactional data helps businesses optimize their operations, uncover hidden patterns, and gain competitive advantages.
This type of data is collected from the internet, whether it's for research purposes or otherwise. It includes publicly available data, such as competitor prices, football scores, or government data. Businesses can use web data to monitor competitors, generate leads, and make important business decisions.
This type of data is produced by objects and machines and is often referred to as the Internet of Things (IoT). It includes data from sensors that measure temperature, humidity, movement, and more. Sensor data helps businesses optimize their processes, reduce costs, and increase efficiency.
The Importance of Data in Business and Society
Data is crucial for both business and society. In business, data helps us make better decisions, optimize our operations, and stay competitive in the market.
For instance, analyzing transactional data helps businesses understand their customers' needs and preferences, which can lead to more effective marketing and increased revenue. In healthcare, analyzing medical data can help doctors diagnose diseases and develop treatments, improving patient outcomes.
In society, data helps us understand and address complex problems, such as climate change, poverty, and inequality. Data can also help us make informed decisions about public policies, such as education and healthcare.
For instance, analyzing student performance data can help educators identify areas where students need more support and tailor their teaching strategies to meet those needs.
If you’re interested in learning more about big data, data collection, or want to start taking advantage of all data has to offer, check out these blogs, courses, companies, and more:
- Flowing Data – run by Dr. Nathan Yau, Ph.D., it has tutorials, visualizations, resources, book recommendations, and humorous discussions on challenges faced by the industry
- FiveThirtyEight – run by data-wiz Nate Silver, it offers data analysis on popular news topics in politics, culture, sports, and economics
- Edwin Chen – the self-named blog from the head data scientist at Dropbox, this blog offers hands-on tips for using algorithms and analysis
- Data Science Weekly – for the latest news in data science, this is the ultimate email newsletter
- No Free Hunch (Kaggle) – hosts a number of predictive modeling competitions. Their competition and data science blog covers all things related to the sport of data science.
- SmartData Collective – an online community moderated by Social Media Today that provides information on the latest trends in business intelligence, data management, and data collection.
- KDnuggets – is a comprehensive resource for anyone with a vested interest in the data science community.
- Data Elixir – is a great roundup of data news across the web, you can get a weekly digest sent straight to your inbox.
- Marcus Borba (CTO Spark) – his feed is stacked with visualizations of complex concepts like the Internet of Things (IoT) and several incarnations of NoSQL
- Lillian Pierson (Author, Data Science for Dummies) – she links to a bevy of informative articles, from news clips on the latest companies taking advantage of Big Data, to helpful blog posts from influencers in both the data science and business space
- Kirk Borne (Principal Data Scientist at BoozAllen) – posts and retweets links to fascinating articles on Big Data and data science
- 40 data mavericks under 40 – this list encompasses the who’s who of the bright and innovative in data and startups
- Udemy – free and paid-for online courses to teach you everything you need to know
- Code School – learn coding online by following these simple step-by-step tutorials and courses
- Decoded – essential introduction to code that unlocks the immense potential of the digital world
- Data Camp – build a solid foundation in data science, and strengthen your R programming skills.
- Coursera – partnering with top universities and organizations to offer courses online
- W3schools – has great online tutorials for learning basic coding and data analysis skills.
- OpenRefine – a data cleaning software that allows you to pre-process your data for analysis.
- WolframAlpha – provides detailed responses to technical searches and does very complex calculations. For business users, it presents information charts and graphs and is excellent for high-level pricing history, commodity information, and topic overviews.
- Import.io – allows you to turn the unstructured data displayed on web pages into structured tables of data that can be accessed over an API.
- Trifacta – clean and wrangle data of files & databases you could not handle in Excel, with easy-to-use statistical tools.
- Tableau – a visualization tool that makes it easy to look at your data in new ways.
- Google Fusion Tables – a versatile tool for data analysis, large data set visualization, and mapping.
- Plot.ly – visualize your data in an easy way to quickly see trends and insights
- Luminoso – identify the relationships between keywords and concepts within your data set and glean insight into product perception.
- BigML – Build a model of your market, with all the variables like pricing, product features, and geography.