80-90% of data in the world is unstructured. Discussing the variants
What is the difference between structured and unstructured data management? Knowledge is power and data is the king. Analysing fields of data can help businesses grow more effectively. Large companies process large data for future scoping and extending business differently. It gives a rough idea of the measurements to take.
Did you know, data usage today is 20 times greater than in the last 5 years? In 2020, 40 zettabytes (40 trillion gigabytes) of data were being used. 90% of it was the result of the last two years only, according to IBM. There are different types of files among them. Big data welcome this data structure management. Without proper management, only drives will be filled and lack effective accessibility.
What is data and big data?
Digitally stored variables in other words, facts and figures are called data. The term “Data” is plural and its singular form is “Datum”. Digital formats like images, videos, charts, numbers, texts, audio can be stored in devices in the format of binary numbers. Computers can only interpret binary (0,1).
Just in 2019, Facebook had 500 TB’s of files uploaded to their servers. Analysing them is not an easy task. What makes it even possible to sort as much as possible is to use tools that are programmed to analyse them, ML, AI, and use the analytics. Popular streaming service Netflix has a consequent 100 M users and suggests new shows or movies to viewers as a feature. They collect customer preference data, playlists, location, age, time, gender, etc. So later they can analyse those and suggest someone at the same age or feature group to watch that specific show. In return, the customer is happy to find the best suggestions for them. At the same time, it is beneficial for Netflix too.
Understand how structured data works
Structured data are the ones that we can easily put in rows and columns. It has predefined values. An image captured by a digital device contains a date, location, size, and other properties that help shape and recognise it. Similar goes for the sales chart. It has the dates of sale and the number of sales. A good example can be an Excel chart or spreadsheet. We can put it in statics to check, on which date we’ve sold the most amount.
Companies shying away from processing data didn’t know how to handle this massive chunk of incoming payloads frequently. Now we have tools to do these things for us.
Is unstructured data hard to handle?
Unstructured data are not pre-defined. Emails, uploaded images on social media like Facebook, Instagram are unstructured. Much unstructured data is handled by artificial intelligence and machine learning. 80-89% of data in the world are unstructured.
Even if sources are the same, it is very difficult to manage this niche of data in a highly scalable environment without proper measurement. And that’s what we’re going to discuss in the last segment of this one.
Innovative strategies for competitive advantage: Semi-structured data
The key to innovation in this data world is to manage structured and unstructured data properly. We have another format, which is called semi-structured data. In past, we couldn’t’ analyse everything, but now we can. There is a blurry line between the two types of data. They have recognisable yet unrecognised properties.
Handling this information can be done in various ways and very effectively. One of them is indexing. So that similar data will be stored in a familiar bucket. Storing them in the proper place can also make unstructured data structured. AI and ML algorithms are being updated to follow and pattern unstructured data.