Think about this scenario – you run an exclusive luxury handbag reseller operation in the Atlanta, Orlando, Tampa, Charlotte, Miami, Houston, and Dallas, TX area from your basement in Austell, Georgia. You have a profile of two of your customers Jane and Sandy who buys a lot of high-end bags from you. What you do know and what other folks don’t know is because the Japanese yen is 130 to 1 US Dollar, you can get Hermes Birkin imported from Tokyo for around $6,000 to $7,000 and resell for $11k to $13k used. You buy the bag because you know it will sell.
The reason you know the Birkin will sell fast is that you have a graph data in a place where as soon as the bag is entered into your inventory, machine learning will look up your most likely clients, Jane and Sandy, and inform them that a new Birkin is ready for sale – so you will have that bag sold by the end of the day, your asking price because you have true data segmentation and automation to act on smart data using graph data technology.
If there is a technology that people are sleeping on, I would say it is graph data. Being able to properly structure data and have the flexibility to uncover patterns and trends gives graph data users an edge over their competitors. Mastering graph data also uncover new revenue streams and can help someone become more profitable. Plus there are big bucks in consulting by being a graph data solution provider to help other organizations structure their data and make decisions.
Toshikiso has an awesome graph platform in our API library and there is already a graph-driven application called Dreams, Never Ends that we have been using internally for several months. Dreams, Never Ends is our Graph DNE engine and some people will say I named it after New Order's first album song and my response is I will not confirm or deny such statements.
Let’s talk about graph technology and how to leverage it. It is very important you understand this technology because, to be honest, I don’t see anybody making it in the 21st century if they do not know or leverage graph data technology.
Overview of Graph Technology
Graph technology is a way to structure data where you break everything into objects and relationships. However, our Graph DNE implementation has some extensions you should be aware of:
Node and Edges. A graph node is any object or subject. A cup of coffee is a node, the café is a node. Edges are the connection between nodes where a café serves a cup of coffee. Then you can structure what a café serves by calling all nodes that are connected via the “serve” edge.
Time Series. This is part of our Graph DNE not seen on other graph engines. You can record events under a node and these are recorded actions. For example, the café served coffee at 1:30 pm is a time-series event. What you can gather from this is to find out how much coffee you served at 1:30 pm? What kind of coffee? What customer? Who made it?
Attributes. This is also part of our Graph DNE not seen on other graph engines. These are attributes that are too vague for a node such as the color or size of a t-shirt. So you can have a node for a t-shirt and you add attributes such as large or extra-large. But you can also look for all blue shirts that are medium and pull up a list for a specific customer and send them an email to show what is in stock for them.
Paradigm Shift in Data Intelligence
The old way of data relationship database where you join one table to another table to create a view gives a limited view of the data you are working with. The graph approach turns every possible data point into a single unit that can pivot on that single unit. That means you can pivot on the name of a person and retrieve their photo or their birthdate or their favorite ice cream. That means if you want to pivot on all the shady characters based on their activities, you can pivot on the scammers, and the charlatans as you keep track of people in your graph data.
There are two real-world scenarios I will be applying graph data in our brands:
Dating Site for High-Value Brothas. A dating site or any matchmaking site needs to use graph data to show a relation of attributes that both parties wish to seek. A brotha wants a chick with a nice figure and a chick with a nice figure wants a brotha with money to blow – those attributes can be pivoted within a graph and match each party to what they want from each other. If you going to do any kind of matchmaking site from job recruitment to roommates, graph data should be your first consideration of technology to implement if you want to stay competitive.
Merchant and the Flow Product Service System. A product-service system is the next-generation e-commerce platform where both products and services are combined as a packaged experience versus just linear product or service selling. However, if we turn each product or service being sold into a graph node and take advantage of the time series component, we can learn when a product is peak selling or slow-selling for a merchant. This allows a merchant to have the intelligence to promote a product that is slow-selling at a small discount to move it off the shelf at a certain time. The merchant can also know which customer nodes are purchasing a product at which time and at what interval and that can allow the merchant to offer a subscription/delivery on a certain product due to having this kind of knowledge from graph data.
I’m pretty sure you are realizing a brotha from the ghetto using pawnshop laptops to program all this tech running a global empire and these cornball clown Black in tech characters over there talking like they special and stuff, right? All those Black in tech phony clowns do is beg and ask for validation and acceptance from White Privilege circles and liberal platforms to make me and you think they are special and chosen. Guess you see what’s real and what’s posing out here, huh?
Opportunities with Graph Data
Not only can you leverage graph data technology but you can create a niche where you consult and help firms leverage graph data as part of their digitalization efforts. Most digitalization efforts need data transformation where they can shift through their data lakes and data silos and have a unified and connected data source and graph technology accomplish this.
Let’s talk about how to implement and leverage graph data.
Turn everything into nodes and edges. Look around your household and the stuff going inside your head and turn all of it into a graph node. Now start connecting the nodes with edges such as the KitchenAid mixer belonging to the cooking node and the kitchen node as appliances. When you do a query later on appliances, all of your kitchenware should show up.
Add attributes to nodes. These are tags such as “need replacing”, “never used” or “stank attitude” that you add to the nodes. What you can do later is a search for the items you never used and decide whether you want to keep or sell them or give them away.
Add timeline to edges. Timelines can be triggered such as if I enter the home office, I scan a QR code that enters a timeline stamp that I entered the home office at a certain time and date. Or if I eat ice cream, I have a homemade website that I recorded I ate ice at a certain time. Then at the end of the week, I can compile how many times I ate ice cream, entered my home office, how many times my girl called me over and over, and analyze this data.
This is what you do for yourself and if you create your own data consulting firm, you transfer all of your client objects into nodes and work on edges and attributes and timelines. Then you consult your clients on data points they may have not realized before. Things such as a bar selling this much top-shelf drink from a certain customer and the customer guests every Thursday. See what we trending toward is businesses are not advertising, they want to tap into their existing data and activity and exploit new opportunities that they may be missing without the proper data.
So to wrap it all up, look at these broke brothas and broke sistas over there following YouTube charlatans and having lightweight chatter conversations before running to their job packing boxes at the Amazon warehouse – better meet that quota they keep raising on them, that’s all I got to say about them. All this brand-new opportunity in technology and solutions that need to be implemented in the Fourth Industrial Revolution and this broke-ass motherf*cker over there engaged in broke petty stuff – leave that fool alone.
You can use graph data to give yourself a competitive edge or consult others to have a competitive edge and help transition them to smart intelligent driven decision-making. You get paid big bucks for that kind of talent and skills and you make big bucks finding opportunities no one has seen before. You can start a new job as a rookie and graph node and edge everything and learn all about your business and suggest money-making opportunities and get bonuses and promotions fast.
You can create your own matchmaking solutions, e-commerce solutions, social credit solutions, and metaverse solutions which all sit on top of graph technology. Toshikiso has graph technology and we releasing a product/platform called Dreams, Nevers Ends that allows you to run from your computer and perform some complex queries of your graph data. This is why we think it is the most essential thing you learn in the 21st century is graph data technology.