Processing information is a huge task if you are dealing with big data. Fortunately, besides the increasing amount of information created every day, there are also tools and software that helps in such titanic task. But first of all, what is Big Data Analytics? It is the examining data to find out customer preferences, market trends, unknown relations, hidden patterns and errors. They all represent the basis of organizations to make decisions based on such well known facts.

Big data analytics technologies and tools

If we mentioned the applications, software, tools and lingua used for Big Data analytics, most people would be at lost. However, if you have surfed in the net, you surely have found that Hadoop and MapReduce are the most popular ones. There are others, such as Text mining (mainly used to sift through data sets in search of patterns and relationships), Statistical Analysis Software that includes predictive analytics to build models for forecasting customer behavior and other future developments, Mainstream BI Software –Machine Learning– which taps algorithms to analyze large data sets, and Deep Learning, a more advanced offshoot of machine learning which are largely used. Best is to get a expert help.

Big data analytics benefits

Some of the benefits driven by specialized big data analytics systems and software are: new revenue opportunities, more effective marketing, better customer service, improved operational efficiency and competitive advantages over rivals.

Of course, just by having the information processed is not an asset; it is the fact of how you manage that information what makes your company standout from the others. There are two main purposes when companies and different organizations analyze big data: in the first place, being able to detect real time events in order to provide adequate solutions and finally, to use historical learning from previous events to predict (though it actually uses both “up to day data” and “historical data”). In other words, such data analytics provide a means of analyzing data in order to draw conclusions and make informed business decisions.

Your organization and some of the big data analytics challenges

There are some data management issues caused by the huge amount of data involved when an organization uses data analytics applications and software. Some of them include data quality, consistency, governance and the drawback of integrating Hadoop, Spark and other big data tools. It is necessary to resource to expertise that knows the right mix of technologies and then put the pieces together for a successful performance.

Tips to become more data driven:

  • Seek a solution that can turn anyone into a data analyst. Find a business solution that has analytical functions and best practices built in.
  • Speedy analysis is critical. Sometimes it is necessary to turn to a specialized company for data-visualization software.
  • Get visual. Find a solution that makes visualizations simple and that has best design practices built in.
  • Rely on the cloud but not exclusively. Look for a solution flexible enough to rely partly on cloud computing and that also for storing data on premises.



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