The average internet user creates .77 gigabytes of data a day. Whether it’s your shopping habits, the articles you read, or conversations with others you; leave a trail of personal data in your wake. This data is incredibly valuable to businesses who want to leverage that information to create targeted marketing campaigns, improve customer service, or simply learn about human behavior and economics. However, studying this glut of data isn’t only about turning a profit. Big data can be used more altruistically to improve resource supply chains to serve underserved areas, model virus transmission to predict the spread of disease, and influence policies designed to protect the environment. The value of data cannot be understated, nor can it be summarized in just a few points. Data is the lifeblood of modern society, and as such is a key currency in business.
If your organization is looking to get an edge by predicting and adapting to consumer trends, then big data might be the answer.
Popularized by Doug Layney in the early 2000s, the term big data refers to extremely large or complex data sets. Due to its massive scale, big data cannot typically be processed by traditional relational databases (data organized in a table structure). Although there is no set threshold regarding size, there are three primary factors that distinguish big data: volume, velocity, and variety.
Volume: Businesses produce massive amounts of data every day. When that volume is too much for ordinary storage solutions (think terabytes or petabytes) to handle efficiently you are generally dealing with Big Data.
Velocity: Digital devices are producing and sending data at unprecedented speeds. The network of digital devices that interact with the web is referred to as the Internet of Things (IoT). Dealing with this high-velocity data in real-time is typically beyond the scope of manual processing or traditional data handling methods.
Variety: Data comes in many disparate forms, including unstructured data, form submissions, numerical data, text documents, emails, and even images. When you need to work with unstructured data or information flowing in from different sources, you probably have a Big Data challenge.
Big data is a deep well of powerful knowledge. When you combine data from thousands (or millions of users), you get a more accurate picture of the business landscape. Getting insight into big data can help your business pick up on unexpected trends. Big data sets can inform decision-making or streamline processes by doing three main things – detect anomalies, find and predict patterns, and find meaningful relationships. Some typical use cases include:
Finding big data sets isn’t particularly difficult. Many free and paid resources offer data of every type to help you analyze and track the latest trends.
There are many great resources for testing, modeling, or cleaning up data. Perhaps you have team members trying to learn Tableau, or you want to better understand how to use AWS machine learning tools. If that’s the case, free data sets can be a great place to start.
Whether you plan to use your own data or work with data provided by another entity, the big question remains, “How do I Use a Big Data Set?”. Just as there are many data sources, there is no shortage of great data tools that can help you dive into big data. Whether you’re cleaning, analyzing, or visualizing data there is certainly something to suit your needs and budget. Ultimately, there is no single right answer or individual tool that allows you leverage big data. Instead, using and applying data to your business is a process that combines many different tools depending on what you’d like to get out of the data. Choosing the right combination of tools begins with asking yourself what the data will be used for:
Answering these questions should help you get a better picture of your data needs. From there you can narrow down the functionality you need. For example, if your focus is on data visualization or you need specific software integrations, that will dictate which data platforms you choose. There are thousands of choices when it comes to data analysis tools, far more than could be covered in the scope of this blog, and that’s why we suggest seeking out the guidance of a data professional in making the choice that’s right for your team. With a wide range of open source options, there may be someone on your team who can get the discovery process started with a low initial investment.
Data will drive the future. Big Data has the potential to help you make more informed decisions, reduce costs, and find profitable business opportunities. Whether you’re trying to forecast next year’s weather or wrestling with how to price your products data analytics can guide you. The speed of business is quickly outpacing the capabilities of manual data analysis. As a result, automation or AI powered by real time analytics is increasingly becoming an essential business strategy.
Looking to get started with big data? Amazon Web Services (AWS) has a wide range of data processing and machine learning tools to get you up and moving. DOMA can help you migrate, process, and visualize your data within the Cloud using AWS tools and Microsoft Business Intelligence (BI).
DOMA Technologies (DOMA) is a software development and digital transformation company whose mission is to change customer lives by lightening their workload through faster and more targeted access to their data. Since 2000, our team of 200+ experts
has helped businesses navigate all aspects of the digital world. We are a dedicated strategic partner for the federal government and private sector clients at every stage of their unique digital transformation journey.
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