According to EY, the value of data is depreciating. $8.2 billions are lost to news, content pieces and advertising collaterals which have no value.

But that can be avoided.

How?

With graph analytics.

 

But what is graph analytics?

Like the general graphs of mathematics, graph analytics help to contemplate and visualize the relationships between two objects. This is done by decoding the direction and the strength of relationships between the objects. These graphs are powerful data structures which represent complex dependencies of the real-life data.

 

Through connected analysis and graph technology, you can:

• Combine and correlate a company’s information
• Model the results as a connected graph to structure the relations
• Apply link and social network analysis for the discovery of new facts and predictions

 

Too much technology?

Let us understand graph analytics with the help of an example. Suppose the case of money laundering has to be recognized. For this, all the bank accounts are taken as nodes (objects) and their relationship is studied. The quantum of transactions or the nature of the relationship between any two bank accounts can predict if they involved in money laundering or not. This is exactly what graph analytics does. It decodes the patterns to predict the future (based on the relationships between two objects).

 

In a nutshell, there are three steps/levels in Graph Analytics:

• Graph Query: Graph query is the relationship between the two objects within the data.
• Graph Algorithm: Graph algorithm is forming a pattern around the nature of the relationship between two objects by applying a functionality.
• Graph Analytics: Graph analytics is applying and decoding functions to grasp the macro and micro level details about the graph.

 

Four types of Graphs Under Graph Analysis:

Path Analysis: This type of analysis can be used to determine the shortest distance between two nodes. The use case of such graphs is to decode supply and distribution chains and help in traffic optimization for smart cities.

Community Analysis: It is a distance and density–based analysis which helps in predicting the future of the relation between two objects. The use case of such graphs is to identify whether a particular social media strategy/community would work or not.

Connectivity Analysis: This sort of analysis helps in determining the flows in the network. The use case of such graphs is to compare connectivity across networks.

Centrality Analysis: This analysis helps in determining the most influential node by analyzing the interactions and impressions in every case. The use case of such graphs is to find the relevancy of a particular influencer for a particular marketing campaign.

Moving on, we list one use case of graph analytics which will help you to understand the concept in a better way.

 

Case Study: Finding the fake bot accounts that are distorting social media marketing

This is done by creating a graph between accounts with retweet counts as a major factor to see how many times these accounts are retweet information from their neighboring accounts.

From such a graph, it becomes easy to find:

• Accounts with a high retweet count
• How other accounts are retweeting them
• Accounts that also get retweets from only some particular bots

With this, companies can decipher fake accounts from real accounts by studying their pattern, structuring the pattern and analyzing it.

 

Conclusion:

The use case of graph analytics is not restricted to a few cases. Graph technology is an excellent tool to discover the truth in data and hence it is rapidly becoming more popular. It assist businesses with nearly accurate predictions which helps them in growing in a scalable manner.

Therefore, we at Avyuct feel that there are no two ways to the fact that, graph analytics, if incorporated effectively, can change the business scenarios in a lot more ways than it can be imagined. We have seen live examples where client’s business was sorted and gave really high numbers in terms of ROI with the help of Graph Analytics.

Yes, we just boosted about our work here but you can surely connect with us to know about the technology.