Network Analytics for Dummies
Sep. 30th, 2019
Let us start this article with a good piece of honesty.
It’s called “Analytics For Dummies” for a good reason. While I certainly don’t mean to insult any of my dear readers, I do want to clarify that this article features only a very basic explanation of what network analytics are and what benefits they bring. I myself am not a professional in this matter, which is why I am well prepared to write a text meant for beginners.
There is no need to be afraid of complicated technical terms or confusing logical problems. We will simply try and explore network analytics together.
The best way to start is always with a basic explanation.
What is network analytics?
Boiled down to a simple sentence, it is the process of gathering data from a network and then, organizing and analyzing said data. This is meant to help to recognize patterns and trends of a network or a whole community. In regards to a community of personal connection, this could be age groups, people joining or leaving your network, industry groups, etc.
But that is only half of the process. Collecting and organizing the data is the task for a basic analytics engine, which will most of the time offer a limited amount of insight in a network, examples described a paragraph earlier. A good network analytics engine will do more.
Besides collecting and comparing the data and visualizing it in an understandable way, it should also suggest changes and improvements to the network. Of course, this depends on the kind of network that is being analyzed, and it might not be possible for all types of communities. But with many business networks, it is possible and beneficial.
In these cases, the analytics engine will compare the current state of the network based on the data it gathered/received, to a model of how the network should be functioning. A simple performance-to-target-comparison. The template, of course, has to be input manually before, but after that is done, the engine can work mostly on its own, spotting problems, discovering trends and suggest measurements.
"Network analytics is a young field and there are still many issues that one needs to face when trying to understand the great mystery that is analytics."
The most relevant one at the current moment is that most programs only feature a solution to one problem and not more than a limited amount of insight in one's connections.
They usually work in silos and only gather and analyze a specific part of the data. A “silo” in the analytic way of speaking is not too far from the original, it describes a confined space in which data is preserved in. For clarification, this is meant in a negative way, for example coworkers not sharing information with each other and ultimately doubling the work for the company.
You can imagine it like looking at the night sky through your window, with the curtains half closed. The star constellations and greater structures are impossible to understand when your view is so restricted.
Many programs only monitor one space or are simply not able to capture the whole network. This forces companies, which have the desire to analyze the entirety of their contacts, to purchase several of those programs to gather all the information there is. The result is a complex ecosystem of solutions that are all working separately, which then requires the analytics team to go through all the various programs and manually compare the results. Ironic, afterall the purpose of the analytics program was to save time of gathering and analyzing data in the first place.
Another problem for many companies is the sheer amount of data held in their network. This especially concerns small companies like start-ups or the ones with specifically large communities. With a growing network the amount of administrative tasks and work that needs to be input, rises exponentially. Just imagine all the contact information, ranging from telephone numbers, addresses or email addresses over availability, jobs, companies and that only for a single one of their contacts. The solution is often endless lists of contact data, stuffed calendars, huge armies of sticky notes, it is a mess.
This is where network analytics is meant to help. By collecting all the data, organizing it and visualizing it in graphs, it’s main purpose is to supply you with the right information to make the right decisions.
That is what analytics is about at the current stage. Network monitoring and management are very time-consuming tasks and on top of that, we humans are not very good at them. With “not good” I mean that our brains think in pictures and are not the greatest at comparing long lists of data and recognizing overall tendencies. Softwares and programs can do that with ease and we have only started to scrape their potential in this regard.
When talking about the future of network analytics, one term is heard quite often, the term of the “adaptive analytics engine”. This refers to an engine, which configures and optimizes itself, based on the conditions, recent trends, and patterns of the networks. The words “machine learning” and “artificial intelligence” may sound threatening and remind us of movies like “terminator”, but in reality, it is far less dangerous.
The analytic engine will simply save a problem scenario that occurred, together with the factors that led to this outcome. In the future, it will then take preventive steps, to either make the scenario impossible, notify its makers early enough or solve the problem on its own, when some of the factors are met. This is called remembering a “context”, the specific circumstances, in which a network anomaly occurred. The engine will seek to avoid or eliminate the possibilities of this context (or one similar and equally problematic) appearing again.
With thriving interconnectedness, flourishing digitalisation and expanding population, the sheer number of entities able to join networks will grow rapidly. Network management and analysis will be in demand more and more often and it is probable and only logical that analytics will (have to) grow to adapt and fulfill the new expectations and challenges.
Our software “nevaal Maps” is not that far, we can’t analyze and improve all your connections yet. But if you are looking for a tool to support you in managing and figuring out your network, we might be able to present a solution to you.
nevaal MapsTM visualizes your contacts and connections, making it easy for you to understand your community and see it ́s true value. Further, all contact information can be gathered and centralized here, so that it becomes simple to find and access them. There will be no need for searching through excel lists or archives anymore, you can simply find all that you are looking for in nevaal MapsTM.
Features to analyse your network are in the making and on the way, but until we can make them available to you, nevaal MapsTM can help you save time on administrative tasks, so you are able to work more efficiently on growing and intensifying your network.
Want to try out nevaal MapsTM? Get started for free! Just click Schedule a Demo and sign up! You won’t regret it!
Additional reading:
NATAŠA PRŽULJ, NOËL MALOD-DOGNIN - Network analytics in the age of big data
Tags:
Ecosystem Management
nevaal Analytics
Follow nevaal
