In the current market scenario, large scale and small scale companies have already realized the importance of Big Data. It is not a mere buzzword anymore, but the new facet of business today – which requires management of large volumes of structured, semi-structured and unstructured data.
But that is not the end. Analyzing the data in a way that brings real business value is what the corporate industry seeks for. Hence,in order to identify trends and patterns, and churn out the valuable things from a massive amount of data, the role of Big Data analytics comes into play.
What is Big Data analytics?
In order to understand how to analyze data, let us understand what Big Data exactly is. Big Data analytics is the process of a data analysis that involves examination of large data sets to find hidden patterns, customer preferences, market trends, unknown correlations and many other business information.
Those analytical findings can generate more effective marketing, enhanced operational efficiency, new revenue opportunities, better customer service, competitive advantages over the rival organizations and many other business opportunities. Business and IT heads who used to report the Big Data management issues on a regular basis are now slowly migrating to big data analytics to solve those problems.
Big Data Analysis
As we have already understood, big data analytics helps the companies in taking more explicitly informed business decisions and hence, generate more business.
Analyzing big data is much beyond just buying a data analytics software because handling only the data analytic technologies is not just the challenge. Well-planned strategies, big data analysis techniques and people with the right set of skills and talent who could leverage the technologies according to the given parameters are also essential for a big data analytics initiative.
On the other hand, buying additional tools for business intelligence beyond an organization’s analytics applications and business intelligence may not even be necessary depending upon the business goals set for a particular project.
The potential pitfalls that can boost up organizations taking initiatives on big data analytics contain many loopholes like, the lack of expertise in internal data analytics and expensiveness of hiring experienced analytics professionals.
Data management, quality and consistency issues are also caused by the amount of information that is involved and its variety. In addition to that, integrating Hadoop systems and data warehouses could be a bit messy, although many vendors now offer software connectors that join big data tools Hadoop with relational databases and other data integration tools (having big data capabilities).
Big Data Analytics Tools
The modern day technologies allow big data analysis using many software tools commonly taken as a part of advanced analytics processes such as predictive analysis, text analysis, data mining and statistical analysis.
The software is available in the open source platform and can be used as big data reporting tools as well. On the other hand, mainstream business intelligence tools and big data visualization tools play an important role in the advanced stage.
Let us discuss different categories of data analysis and reporting tools, and how they can be deployed to initialize and advance the process of big data analysis.
1. Open source big data tools
- Jaspersoft BI tools
Jaspersoft was originally created for report generation and now it is gaining popularity as one of the best open source tools for business intelligence, that generates reports by extracting information from database columns.
This software is one of the highly advanced reporting tools for big data deployed already in the business market for creating PDFs out of SQL tables for everyone to scrutinize at business meetings. It forms a bridge between report generating software and big data storage houses.
Jaspersoft now offers software to extract data from most of the major storage platforms such as Cassandra, MondoDB, Riak, Redis, Neo4J, and CouchDB. Once the data is sucked up, Jaspersoft’s server converts that into interactive tables and graphs.
The reports thus generated are highly sophisticated interactive tools which help the user drill down as much as possible and fetch as many details as required. This stands at the top of the list of business intelligence tools and Jaspersoft is attempting to make it even easier to use the sophisticated reports.
Basically, it doesn’t offer particularly a new vision to look at data, all it offers is a highly sophisticated form of accessing data located in new storage houses.
- Talend Open Studio
Talend studio is an open-source software that offers an eclipse-based IDE to string data processing jobs with Hadoop. It is mainly used for data integration, data quality, and data management, with subroutines involved in these jobs.
It allows the user to drag and drop little icons onto a canvas. Its components also allow the user to fetch RSS feeds and proxy them as and when needed. There are numerous components to gather information and others to do things like a “”fuzzy match”” prior to the output of results.
Stringing the data processing jobs together visually with this tool could be easier once you get to know what the components can do and what not.
- Skytree Server
Skytree is one of the best open source big data tools that bring you a bundle,which performs like the highly advanced forms of machine-learning algorithms. However, the user needs to take special care about typing the right command on the command line.
Skytree is specially designed to run a number of complex machine-learning algorithms on the data using an implementation, about 10,000 times faster than other packages. Its intelligence system searches ‘system data’ by looking for clusters formed by mathematically similar items. Then it inverts the data to identify outliners which could possibly be problems, opportunities or both.
It comes in both paid and free versions. Even the free version of this tool offers the same algorithms as that of the proprietary version. The only limitation is, data sets limited to 100,000 rows.
2. Big data visualization tools
Data visualization today has gone far more than just charts and graphs used in Excel Sheets. Now it has gone to more advanced levels such as infographics, geographic maps, dials and gauges, heat maps, sparklines, detailed bars, pie and ever charts. Sometimes the images might include interactive capabilities that enable the users to manipulate or drill into the data for querying or analyzing.
Most of the business intelligence software vendors nowadays embed big data visualization tools into their products, either by developing the visualization technologies on their own or sourcing it from the companies dealing with visualization.
Let’s discuss one of the most preferred data visualization tools – Tableau Desktop and Server. It is a visualization software that eases the way you look at your data in a variety of new ways, then slices it and makes it look different once again!
You can also intermix the data and check it in yet another light. This tool is perfectly optimized to give the user all the columns for the data and enables him/her to mix them before integrating them with one of the hundreds of default graphical templates.
3. Big data reporting tools
- Pentaho Business Analytics
Pentaho emerged as a report generating engine. Just like Jaspersoft, it extracts information from the new sources and makes analyzing big data easy.
Pentaho’s tools can be easily linked to the most popular NoSQL databases such as MongoDB and Cassandra. It features a very user-friendly sorting and sifting table which comes in handy when the user wants to know who is spending the most amount of time on a website. Thus, it is gaining much popularity among the web analysts as one of the best big data analytics reporting tools.
- Splunk
Splunk has unique features as compared to other big data analytics tools. It is something more than the mainstream big data reporting tools or a mere collection of AI routines, although it covers most of that.
It creates an index of data as if it were a block of text or an entire book. Despite the fact that databases also build indices, Splunk’s approach is almost like a text search process and the best part is, this sort of indexing is amazingly flexible.
Splunk is sold in multiple packages:
i.) For monitoring Microsoft exchange server;
ii.) Detecting web attacks.
The index created by Splunk helps in establishing a correlation between data in these and several other server-side scenarios.
The selection of technology/tool is just a part of the big data project. Experts say that evaluation of the potential business value, which a big data software can offer, keeping long-term objectives in mind, is a very crucial step.
the tools and the information you provided is really good. Because of this we come to know about the data visualization and reporting tool as well.
Thanks for writing this great article! It’s very informative, and you included some great links to an equally great article. Great read!