If you want to use big data analytics, it is necessary for you to learn how to use the big data tools and how to analyze the same. Big Data actually refers to the large volumes of unstructured and structured data, which are analyzed to derive relevant insights from it. These insights extracted using advanced big data technologies can benefit companies in an efficient decision-making process by giving them quick and relevant answers to their queries. The same can also help them make important business decisions, by helping them make better choices. Today, companies across the world are making use of big data analytics tools to capitalize on the potential offered by such technologies. Hence, if you too want to be in the thick of things in the digital space, it is important that you learn how to learn big data.
Today, there are two types of big data analytics tools available in the market. These tools include semi-structured and non-structured analytics tools. While the former is ideal for simple and basic decision support, the latter is more ideal for industries that need to make a lot of inferences from their data. Hence, it is important for you to choose the right tool depending on the kind of analytics required by your business.
There are mainly three types of big data analytics tools available in the market. The first one is unstructured. In this case, it means the data has not been subject to any sort of filtering or pre-processing. Since unstructured data sets are usually larger than structured ones, they tend to make more sense. However, unstructured big data analytics is generally used for niche or smaller organizations, where there are limited resources and also a limited amount of data to work with. Since the results of unstructured big data analytics cannot be monetized unlike structured analytics, they are often used to support strategic decision making in organizations.
Another tool used for analyzing unstructured big data is Hadoop. It is an open source platform based on the Map-reduce framework that is used for managing large collection of data on large clusters. In fact, Hadoop is developed for applications that require a high degree of parallelism along with high throughput. Hadoop supports different kinds of data processing including batch, streaming, and grid. Hence, if you are looking for unstructured big data analytics, Hadoop is one of the suitable options. Like Hadoop, there are different ways to utilize Hadoop data processing applications.
The traditional data processing techniques include batch processing, streaming and grid processing techniques. You can also make use of other special toolkits for analyzing large volumes of unprocessed data. Examples of these include SpatialRank algorithm, corpus selection, and text mining. However, even if you are operating on a small scale, you can also make use of distributed computing. This will allow you to run your analytics tasks across a number of nodes on the cloud.
When it comes to large volumes of unprocessed data, you should prefer data processing techniques that are made specifically for large volumes of unprocessed data. The first suitable option for your needs is the established Hadoop platform. The Hadoop community provides several libraries and tools including Hadoop Enterprise Kit (HES), the Map-reduce framework, and the Hadoop Distributed Data Analytics Tool (HDDM).
In case you are running on small scale, you can also consider the use of web-based data analysis tools like Hadoop. As web-based tools are not too expensive, they are quite popular among small and medium size enterprises. Like Hadoop, you can also make use of the Map Reduce framework for data processing. The Map Reduce framework is again an established resource type used by the Hadoop community. In addition to that, the Java framework is also another option for running your analytical tasks across the web.
Finally, it is not a must for you to hire an expert in the industry to mentor you on how to learn Big Data. Since you are still a beginner, you can follow the recommended courses put together by industry experts. If you are feeling somewhat adventurous, you can take the help of social media sites like Facebook and Twitter to interact with industry experts and other users to get answers to your questions. Social media sites are perfect platforms to meet up with industry experts. In addition to that, if you can also attend a few online training sessions, you can further enhance your skills on the use of big data.