The reality is
that there are many different types of data, with various purposes for
different business goals. Below, the most important types of data for your business will
be explained.
Big
Data
Big Data is a term heard often in the last couple of years. It is data
characterized by its volume, variety, and velocity. This means that it is so
voluminous and complex that it cannot be analyzed with traditional business
intelligence tools. In the last decade, companies were all about learning to
deal with Big Data and using it to make better-informed business
decisions.
Big Data comes from everywhere and it is nothing new. However, it stays
new because the definition and structure of big data are constantly changing.
This happens due to the rapid and constant growth of data. For example, Big
Data used to be expressed in terabytes, while now it is expressed in
exabytes.
Smart
Data
In contrast to Big Data, Smart Data is actionable and does
make sense, and has a clear purpose. It is not about the volume of the data you
are collecting - it is about the actions you take in response to that data. It
is a concept that developed along with the development of algorithm-based
technologies such as artificial intelligence and machine learning.
Smart Data is usually generated close to the data source, using edge
computing technologies. So instead of collecting all data from a source, we
process the data in the source to end dumping in our data lake only the
valuable data; the Smart Data.
Dark
Data
Dark Data is the data that lies below the surface, hiding within
the company's internal networks and holding piles of relevant information that
can be moved to the data lake and generate vital business and operational
insights. This type of data forms the biggest part of all existing data.
According to KPMG research, 80% of data is Dark Data. This means there are a
lot of hidden opportunities lying in the hollows of Dark Data.
The many sources that were being ignored or hard to access, can now be
treated as data gold mines. This is possible due to cutting-edge technology
that can reach into the places that hold Dark Data.
Machine
Data
Simply put, Machine Data is the data created by the systems,
technologies, and infrastructure powering modern businesses. It comes from
places like control and operational systems, sensors and Internet of Things,
and your industrial network.
If made accessible and usable, Machine Data is argued to be able to help
organizations troubleshoot problems, identify threats and use machine learning
to help predict future issues.
Even if you are a machine manufacturer or you have assets and devices in
your business hiding relevant operational information, being able to gather
device data for observability and analysis of usage and performance is a must.
With Machine Data, you can feed any compelling cloud analytics and advanced
services systems.
Transaction
Data
This is the most basic form of data, and easiest to understand. This is
data describing an event or business activity. It describes orders, invoices,
production activities, hiring and firing employees, etc.
Master
Data
Master Data is the key element for transactional data. Master Data
describes places, parties, and things (products, items) involved in the
activity.
Reference
Data
Reference Data is a subset of Master Data. It is usually standardized
data that is governed by certain codification. It is not so difficult to
understand Reference Data. It is data that defines values to be used by other data
fields. These values are often consistent and do not change much over time.
Examples of Reference Data are units of measurements, country codes, corporate
codes.
Reporting
Data
It is an aggregated data compiled for the purpose of analytics and
reporting. This data consists of Transactional, Master, and Reference Data.
Metadata
Metadata is the term used to refer to data that describes other data. In
a more concrete explanation, Metadata is the data that describes the structure
of and some meaning about other data. It explains definitions of data that you
might not see at first sight, such as usage of data, creators of data, users of
data, relations of data. You could see it as a little book that contains all
you need to know about your data. Simply put, Metadata is data about
data.
Conclusion
As you have understood by now, there are many different types of data. Each type of data has relations to another type, and each type has a different, beneficial, purpose. Understanding the benefit and purpose of each type will help your business with data collection, analytics, and business decisions.
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