Recent
years have seen
emergence of cloud
computing platforms which can be used
as utility infrastructures for performing large-scale
data analytics. Many data analytics applications require processing of large-scale graph data. As the
sources, types, and amounts of data continue to expand, so will the need for
different kinds of analytics to make something of that data. Unfortunately,
there is not a one-size-fits-all approach to analytics -- no magic pill that
will get your organization the insight it needs to stay competitive. Graph
analytics has emerged as the new hot topic, but to what end? What is the impact
of graph analytics technology on organizations seeking to discover the cause,
effect, and influence of events on business outcomes? Graph Analytics is a
rapidly developing area where a combination of graph-theoretic, statistical,
and database techniques are applied
to model, store, retrieve, and perform
analyses on graph-structured data. These techniques enable us to understand the
structure of a network and how it changes in different conditions. They can
also find paths between pairs of entities that satisfy different constraints,
identify clusters or closely interacting subgroups inside a graph, or find
subgraphs that are similar to a given pattern.
to model, store, retrieve, and perform
analyses on graph-structured data. These techniques enable us to understand the
structure of a network and how it changes in different conditions. They can
also find paths between pairs of entities that satisfy different constraints,
identify clusters or closely interacting subgroups inside a graph, or find
subgraphs that are similar to a given pattern.
Link to article: https://infocus.emc.com/william_schmarzo/how-can-graph-analytics-uncover-valuable-insights-about-data/
1) why we use graph ?
2) Computer software for graphs?
3) Graph analysis will push big data evolution to the next plateau of scale and sophistication?
We use graphs to provide us more flesible view over our data. Graph analytics provide useful tools that we can use against these vast amounts of social media and sensor-based data to uncover new insights about the relationships between our customers, products, and operations. Graph analytics allows us to get new, more actionable, more relevant answers to many of our traditional questions about our business. It seems like in the Big Data world, new tools and new algorithms are being developed all the time to help the business stakeholders optimize their key business processes and uncover new monetization opportunities.
ReplyDeleteThank you for this good explication, and add also Graph analytics leverage graph structures to understand, codify, and visualize relationships that exist between people or devices in a network. Graph analytics, built on the mathematics of graph theory, is used to model pairwise relationships between people, objects, or nodes in a network. It can uncover insights about the strength and direction of the relationship
Delete1) why we use graph ?
ReplyDeleteIs it mathemathical question? If not, we are using graphs for linked data. Nowadays, we are leaving in a connected world. Graph is a good representation to visualize those connections.
2) Computer software for graphs?
I must say this is a bit inaccurate. Computer software for modeling, storing, drawing ? I'm using Neo4j from time to time to store, model and query complex graphs.
3) Graph analysis will push big data evolution to the next plateau of scale and sophistication?
Yes and No. Yes, because it's easier to model and query data with many connections, e.g. DNA. No, when you are storing flat data. We can use better database models for flat data. This really depends, what are going to store.
Is it mathematical question?? yes, us we know that the big problem related to data analytics can be resolved with a mathematical theory,and for this reason the data scientist used (R, Matlab, Gauss, etc).
DeleteGraph Analytics is a rapidly developing area where a combination of graph-theoretic, statistical, and database techniques are applied to model, store, retrieve, and perform analyses on graph-structured data. These techniques enable us to understand the structure of a network and how it changes in different conditions. They can also find paths between pairs of entities that satisfy different constraints, identify clusters or closely interacting subgroups inside a graph, or find subgraphs that are similar to a given pattern.
I’m intrigued by graph analytics. It’s a wonderful analytic tool to uncover insights about customer, product and device/node relationships buried inside social media, telecommunications, healthcare, and computer networks. I wanted to learn more about graph analytics and explore some specific use cases where the use of graph analytics can lead to new customer, product, campaign, and operational insights.
ReplyDeletewe can learn graph analytics, but first of all we need to have a database background.and for explore some specific use cases, the organizations worldwide are starting to infuse operations with data science's graph analysis approach. Use of graph databases can significantly reduce any support role played by data scientists. Information architects and analytics leaders should understand the costs and opportunities both present.
DeleteI’m intrigued by graph analytics. It’s a wonderful analytic tool to uncover insights about customer, product and device/node relationships buried inside social media, telecommunications, healthcare, and computer networks. I wanted to learn more about graph analytics and explore some specific use cases where the use of graph analytics can lead to new customer, product, campaign, and operational insights.
ReplyDelete) why we use graph ?
ReplyDeleteFor many of things, (for example for make route from one location to other
2) Computer software for graphs?
We have a lot of software for graphs , for example prism
3) Graph analysis will push big data evolution to the next plateau of scale and sophistication?
Maybe Graph analysis will push big data evolution
Thank you Iwo, for more understand graph analytics. What do you do to solve problems that involve complex relationship patterns and require detailed link analysis? Enter graph analytics. Graph analytics can help to mine this wealth of relationship data to uncover consumers’ interests, passions, affiliations and associations.
Delete1) why we use graph ?
ReplyDeleteBecause that how our society works and graphs are better suited for social simulations. Also they provide for us more flexible way of data analytics.
2) Computer software for graphs?
The most popular will be Neo4J with it's Cypher language. The other one will be Titan (wich in my opinion is quite better then Neo4J). Also Facebook has got his own implementation of graph database.
3) Graph analysis will push big data evolution to the next plateau of scale and sophistication?
In this question I totally agree with Mateusz P. My answer is the same. I will just add that when it comes to NoSQL databases you have to know what you will be storing, this kind of databases are not suited to handle all use cases (as Relational Databases can).
Sorry Tomasz, I not agree with you about Titan. Neo4j it's the best for all time.Neo4j's Cypher query language is the only declarative query language built expressly for property graphs. It takes all of the lessons learned from our 13-year old native Java API (which was the basis for Blueprints, which some of the other graph databases have since adopted) and rolls them into a next-generation language. Cypher is a great way to learn graphs, and to develop applications; and there's always the native Java API if you have special needs or value "bare metal" performance (i.e. sub millisecond vs. single-digit millisecond) performance above convenience. Neo4j is built from the ground up to support graphs, and has a graph storage engine that is built to store graphs; unlike some of the more recent additions to the graph database ecosystem, which are architected as graph libraries on top of non-graph databases, and are subject to some of the inherent limitations. (e.g. FlockDB, because it is based on MySQL, will still be very slow for anything greater than one hop.)
DeleteHi!
ReplyDeleteInteresting subject. It looks like graphs have a potential to be used in so many fields. The first that comes to mind is social media, but it is kind of obvious. Also medicine, biology, travel, industry can benefit from from them. I didn't work with graphs, so I am not able to discuss about software. I have heard about already mentioned Neo4j.
Graphs seem to be promising technology.
From college I remember that we used graphs to deal with the problem of the traveling salesman. Prism for example mentioned by Iwo. Graphs are definitely very important for big data evolution.
ReplyDeleteGraph databases are more flexible that relational ones. They can store data and relations that would require large structures with sparsely filled attributes. Market's leading tools, such as Neo4j mentioned before, come with powerful and easy to use features, they are well documented and learning curve is quite shallow.
ReplyDeleteOf course it's not an universal tool for every problem, sometimes simple h2 database can get the job done.
1) why we use graph ?
ReplyDeleteIn some domains it is easier to interpret and compute data from many connected objects with a graph-based model. Social aspect is important in many applications and it is natural to use graphs instead of tuples in those cases.
2) Computer software for graphs?
There are a lot. I have some experience with Neo4j graph database and tools to manage data.
3) Graph analysis will push big data evolution to the next plateau of scale and sophistication?
It depends. It is useful but there are a lot of disadvantages especially with "big data". Scaling is really difficult with graph databases.
I also agree that graph technology is promising science. I'm unfortunately not specialize in graphs however in future it might change. I would like to read about this science from another source than presented link in introduction to this subject. Especially I'm very interested in software which data presentation.
ReplyDeleteHey, thanks for sharing this information with us. As for your questions:
ReplyDelete1. We use graphs to present data in a more readable way (although that depends). Sometimes we can see relations between data much simpler than by other means of their presentation.
2. Do you want us to give some examples? Depends what kind of graphs you want, however you can try MS Visio. ;)
3. That's a bold statement to make, we are not certain about that.
Monem :) Honestly, I don't know much about graph analytics and I cannot answer a question posted this way :(. It probably is very good method and there are sophisticated software available for it but I don't know it and I am not familiar with the subject.
ReplyDelete1) why we use graph ?
ReplyDeleteGraph are very good way to visualize data. Terabytes of data are not understandable for people. Therefore we are using this kind of representation to give human a possibility to take a fast decision.
2) Computer software for graphs?
Prom software prepares a graph from event logs.
3) Graph analysis will push big data evolution to the next plateau of scale and sophistication?
It is very hard question. There is a lot of fields where expectations regarded with graphs are very high. In my opinion graphs have potential but are they lead to breakthrough? I leave this question opened :)
This comment has been removed by the author.
ReplyDelete1) why the use graph?
ReplyDeleteGraphs are more readable than other forms of presentation and working with graphs, we see more dependencies. In addition, analysis of the graphs it is less time-consuming.
2) Computer software for graphs?
There are a lot of programs for graphical presentation. I think that the more popular of these is Neo4J
Graph analysis will push big data evolution to the next plateau of scale and sophistication?
I don't know anythink about this.
Graphs are useful to show the relevant data and emphasize the meaning of some important factor. They are easy to read and more friendly than long, scientific text without pictures. I don't know any special programs to work with graphs, maybe except those included in Microsoft Excel or Visio. Sometimes, I use third part frameworks that allows to create the graph in programs I write. There is also Neo4J, mentioned by Wiesław (by the way, the Neo4J is a graph database, not a program, right?). Graphs are not something new, I think that something else will push big data evolution to the next "level".
ReplyDelete