What’s the Deal with Data?

Data is the lifeblood of cloud computing. Now it is no longer enough to have a data warehouse. Your business also needs a data lake. As cloud capabilities and digital transformation continue to expand and infiltrate our lives, it can be helpful to understand the different types of data and how the data is being used in the world of cloud and edge computing.

Big Data

We hear the term big data often. But what exactly is it? Big data is usually defined as large, diverse datasets that do not fit into a standardized relational database for processing and analysis. Both human and machine processes create the data.

Rob Thomas, general manager for IBM Analytics provides the following explanation of big data.

“While definitions of ‘big data’ may differ slightly, at the root of each are very large, diverse data sets that include structured, semi-structured and unstructured data, from different sources and in different volumes, from terabytes to zettabytes. It’s about datasets so large and diverse that it’s difficult, if not impossible, for traditional relational databases to capture, manage, and process them with low-latency.”  He hypothesizes that big data is a a really big deal because data is the fuel needed for machine learning and machine learning makes is responsible for creating the blocks we use to build artificial intelligence.  

Machine Data

Machine data can best be described as the digital dust particles left behind by the systems, technologies, and infrastructure that power modern businesses.

Think back on a typical day in your life. You get up and drive to the office in your connected car. You use your key card to gain entry to your place of business, then you log on to your computer, make a few phone calls, respond to the emails in your inbox, and access several applications. Every interaction with a machine and every activity you perform creates a wealth of machine data in various formats.

Machine data includes data from a broad array of different sources. It is extremely valuable because it contains an accurate time record of all the activity and behavior of applications, servers, networks, customers, users, transactions, and mobile devices.

When machine data is available and provided in a format an organization can use, it can help them troubleshoot problems, identify security threats and use machine learning to predict future trends and issues.

Structured, Unstructured, and Semi-Structured Data

How do we determine what data is structured and what data is unstructured? We classify data as structured or unstructured by whether the data has a pre-defined data model and whether it’s organized in a pre-defined way. Unstructured data, therefore, does not have any recognizable structure. It is raw data. This raw data can be textual or non-textual and include dates, numbers, and facts. There is a category of data referred to as loosely structured data. This is when data sources include a structure, but not all of the data set follows the same format.

Dark Data

Businesses are constantly collecting data and information assets. When the data and information assets are set aside and not utilized apart from being processed and stored this type of data is referred to as dark data. 

Real Time Data

Real-time data refers to computing that happens about as fast as a human being is capable of perceiving. Basically, it means data is available immediately without waiting. Real-time data is important because technologies such as edge computing, smart technologies, and 5G rely on instantaneous data.

Real-time data is essential for smart technology-specifically smart cities where real-time data is used with everything from dispatching emergency resources in a road crash to traffic control. Real time data also provides a better link between consumers and businesses. It allows companies to offer their customers the most relevant products and services at exact moments based upon location and preferences. We are only beginning to realize the power of real-time data in our daily lives.

Data is driving the evolution of cloud computing and more. It truly is the engine behind the machines.

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Jul 16 21
Christina Zumwalt