Data is here, data is there! There’s possibly no field all across the world that doesn’t deal with data. Also, the extent to which this data is increasing exponentially is surely worth a mention. It is because of this that a new term called “big data” has been coined. Gone are the days when data was limited to megabytes and gigabytes. Today, every other person talks about data in terabytes. This data is meaningless unless one is able to process it in such a manner that it is possible to make decisions out of it.
Having said that, the fact that dealing with such an enormous amount of data to draw convincing conclusions isn’t a simple task at all. This is exactly where data tools come handy. There is a long list of such tools available to make the best of information. Here are some of the best big data tools that have worked wonders for a lot of industries and organizations.
Best Big Data Tools
Big data and Hadoop kind of go hand in hand. Hadoop is an open-source framework and boasts of great processing power. It is one of those platforms that offer massive storage for large amounts of data. It is known to handle concurrent tasks and jobs seamlessly. The world’s top companies make use of Hadoop as they have a voluminous amount of data to deal with.
With Hadoop, it is now possible to cluster multiple computers to analyze the datasets simultaneously. This eliminates the necessity of a large system to store and process data. Simply put, Hadoop is the most commonly used software that handles an enormous amount of data. It is written in Java. One area where Hadoop is extensively used is in Research and Development. This data tool is highly scalable and can be quickly accessed as well.
The storm is yet another open-source framework that boasts of being incorporated with a distributed real-time, fault-tolerant processing system. It is extremely fast in processing data. Majorly, Storm has seen wide applications in the field of cybersecurity, threat detection, real time customer service management, quality assurance, pricing, supply chain optimization, music applications, transportation, etc.
Storm mainly makes use of 5 key elements to process big data – Tuples, streams, spouts, bolts and lastly topologies. Tuple is a data structure that stores data of the form integers, characters, strings, etc. An unbounded sequence of tuples results in a stream. Spout would read data from different sources and the output so obtained is a tuple. A bolt now engages in processing this tuple. Lastly, a topology is a visual representation of spouts and bolts.
Storm is user-friendly, scalable, and robust, generates genuine results and is flexible to the extent that it assists any programming language. Also, Storm guarantees processing every tuple.
Out of all the big data tools that are available, MongoDB is the best when it comes to dealing with data sets that change or vary frequently. It can store data of any type like integers, Booleans, arrays, strings, characters, etc. It is considered to be one of the best alternatives available to modern databases. Data related to mobile applications, product catalogs, and content management systems are best dealt with by MongoDB. This tool stores data in the form of documents rather than rows and columns thus making it very flexible.
If cleaning data and then converting it into different formats is the objective, then OpenRefine is the one big data tool that best fits here. No doubt, the data that one can store and process using this tool can be huge within a matter of a few seconds. It is an extremely powerful tool to deal with messy data. Wondering what’s more that this tool has to offer? Well, this is available in more than 15 languages. Not just that. It is possible to extend the data set to various web services as well.
All the big players in the market like Netflix, Cisco, Twitter, Accenture, Yahoo, etc. make use of this tool to handle data beyond imagination. Having said that, this big data tool made its existence as a NoSQL solution and was first developed by Facebook.
This tool finds its usage in those areas and by those companies that cannot afford losing their data even when the data centre is down. It employs CQL (Cassandra Structure Language) to interact with the database to deliver high availability. It boasts of a Masterclass architecture because of which it is possible to read and write on any node.
Cassandra supports automated data replication. There’s not a single point of failure observed and even if the node doesn’t work as desired, data stored on other nodes are still available and put into the best possible use. Also, it is possible to detect and recover the failed nodes very easily. No wonder why this tool is one of the most reliable big data tools.
All the statistical analysis can be very well taken care of by this tool. It has its own library called CRAN which is the Comprehensive R Archive Network. This network boasts of over 9000 modules and algorithms for statistical analysis. Also, the best part is, the user need not be a statistical expert. Written in C and Fortran, this tool produces the data analysis results in the forms of both – graphs and text.
Let’s Sum Up
There are a plethora of options available which the various companies can choose from to deal with data that just keeps increasing with every passing day. Big data tools not only store data but also process them way too fast and provide you with results that help in taking better decisions ahead. From the organizations point of view, these big data tools aid in a number of ways. The companies are now able to understand their customers better, make better decisions, develop high quality solutions and also increase their profits. Thus, investing in the right tool backed by a strong research can never go wrong.