Unlocking business value from data
1. Unlocking business value from data
Unlocking the value of data is central to digital transformation. To generate insights, you might need to combine different types of data. However, not all data is created and organized the same way. Data can be categorized into three main types: structured, semi-structured, and unstructured. Structured data is highly organized and well-defined. It’s typically stored in a table with relationships between the different rows and columns, like in a spreadsheet or database. Because structured data is organized in this way, it is easy to analyze. For example, it’s common for organizations to use structured data in customer relationship management tools, or CRMs, as they follow customer behavior patterns and trends. Semi-structured data falls somewhere in between structured and unstructured data. It’s organized into a hierarchy, but without full differentiation or any particular ordering. Examples include emails, HTML, JSON, and XML files. Although this data type doesn’t have a formal structure, it contains tags or other markers that make it easier to analyze than unstructured data. Unstructured data is information that either doesn’t have a predefined data model or isn’t organized in a predefined manner. Categories include: Text, which is the most common, and is often generated and collected from sources like documents, presentations, or even social media posts. Data files, like images, audio files, and videos. And infrastructure activity and performance data, like log files from servers, networks, and applications or output data from Internet of Things (IoT) sensors. Organizations can use unstructured data in many ways. For example, a marketing team might analyze social media posts to identify sentiment toward a brand. Or customer service teams might train automated chatbots to augment support staff by analyzing language in customer communications and providing interactive responses. But in general, unstructured data has historically been difficult to analyze. According to Harvard Business Review, on average less than 1% of an organization’s unstructured data is analyzed or used at all. Until recently, tools to tap the potential of unstructured data were either unavailable or prohibitively expensive and complex. What makes this statistic even more concerning is that, according to Gartner research, unstructured data represents 80% to 90% of all new enterprise data. This reveals a staggering gap between the data being generated and the value that it's providing. But, cloud technology has changed that. With the right cloud tools, businesses can extract value from unstructured data by using machine learning to discover trends, or even using application programming interfaces, or APIs, to extract structure from the data. An example of an API is Google Cloud’s Vision API, which uses machine learning to detect products within a picture and can then even label the picture to describe its contents. Understanding the different types of data available can help organizations define what’s possible with the data solutions they have. One of the transformative powers of the cloud is how it can unlock value from structured and the previously untapped, unstructured data.2. Let's practice!
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