Data! Data!… We can’t make bricks without clay. And data is exactly that – the clay from which you can make the bricks. As we have said in our previous article, data is the foundation of all systems, software, Artificial Intelligence, Machine Learning etc.
We are witnesses of a rapidly changing world, a change that is technology-driven. Starting from word of mouth, preaching, evangelizing, written word on papyrus to books and now we have the world of information at the click of a button or a swipe. If we measure the data that has been produced in the last decade, the number will be at least a dozen times higher than the data of our entire history combined. LoriLewis created an infographic that perfectly shows what happens in one Internet minute in 2019 (ref. LoriLewis):
As you can see there are a lot of emails sent in one minute, a lot of Gifs served, Snaps created, Facebook loggings etc. The one Internet minute infographic shows that each one of us can be called a data production facility — data that is tracked and stored on devices on cloud services from different providers around the globe. All this data is used for various purposes. So let’s dive deeper into data!
But, what is data?
- a piece of information
- facts and statistics collected together for reference of analysis
- quantities, characters, or symbols, on which operations are performed by a computer, which may be stored and transmitted in the form of electrical signals and recorded on magnetic, optical or mechanical recording media. (ref. https://www.answers.com/Q/Electrical_stimulation_studies_like_the_one_performed_by_Dr_Delgado_who_made_a_bull_stop_charging_and_turn_to_the_right_have_provided_psychologists_with_what_types_of_knowledge)
So data refers to pieces of information from various sources and formats, created with a purpose. Although most of the attention nowadays goes to Artificial Intelligence, you should be aware that without data, you can’t have any analysis or prediction using algorithms. So to navigate to this field, organizations need to rethink their data and analytics strategies. But first, focus on data.
What are the sources of data?
Well, let’s start with you! Yes, you, don’t be modest! You are a little data factory, aren’t you?! You call, text, send Emoji’s, record videos, shoot pictures, send out Tweets, Instagram posts, LinkedIn messages, e-mail, Gifs, record weight, heart rate, what you have been eating, calories, likes and dislikes, reactions, comments, and there is a lot more where that came from. Then inside and on you, we have some genomics data, this data is all tied to your DNA. Walking around we have cameras and videos recording you, sensors and motion trackers monitoring your movement, especially when you are at a bank or an ATM. Inputting your PIN and redrawing cash generates machine data which is sent to the central bank data storage.
Hold up, are your eyes still pointed towards the text or are you getting dizzy?
All this data coming from the operation of an organization, produced by the primary and secondary processes is data that can be divided into financial, marketing & sales, operational, HR, employee and IT system data. All tied to other companies producing petabytes of data coming from their crop machines, field sensors, drones, sorting machines, autonomous welding robots, human registration applications, and operating systems. As you can notice, we have a lot of data circling each second of the day.
What type of data are there?
At the highest level, there are two types of data, qualitative data, and quantitative data.
Quantitative data refers to digits/numbers and things that are measured objectively such as price, length, temperature, volume et cetera.
Qualitative data refers to characters and descriptions, nonnumerical; it is the data that characterizes, like hair color.
And to make it a bit complex well, we have structured, semi-structured and unstructured data. But also dark data, yes come to the dark side we have cookies. The definition boils down to whether the data has a predefined data model and whether it’s organized in a predefined way.
The funny thing about dark data is the fact that it is a data that is created as a sideproduct of the primary process and is commonly not used.
Analyst house Gartner Inc. describes dark data as, “Information assets that an organization collects, processes and stores in the course of its regular business activity, but generally fails to use for other purposes.”
About 90% of all world data is dark data.
Why is data important for your organization?
Data, data, data is meaningless unless it is information upon which we can make a decision.
Sadly, even though it is 2019 most of the organizations are currently not equipped to handle the immense volumes of data coming from various described sources and are struggling to effectively collect, manage and analyze the data across their companies ecosystem. Without the right organizational structure and processes in place, the tremendous valuable insights from all of this data are at risk.
This leaves organizations missing a critical opportunity to gain a competitive advantage due to the volumes of product performances and usage of data that they are not fully leveraging.
The benefits can be gained when using data from various sources to answer business challenges, problems or analyze possible opportunities for markets, products, production or operational improvement. All of these can be beneficial for a company! But to learn what the right strategy is and how you can employ data, you have to wait for the next article!
Drop a comment or a question, and we will be sure to answer it!