Five trends in big data analytics
Big Data is the new buzzword for companies around the world. The task of collecting, saving, securing & utilising data to provide better services & products to customers is a race that no company wants to lose. No doubt that the entire process is time consuming. But this is also the reason that big data analytics is one of the fastest growing technology trends. Big data analytics are in demand with high salary packages on offer. So, we identify for you the top five trends in big data analytics this year.
Moving to the Cloud Gone are the days when data was stored & accessed locally on large clunky servers. Now, more complex & sophisticated technologies are available for processing data in the cloud. Companies like Amazon Redshift provide remote, petabyte-scale data warehouses to efficiently analyze big data for companies using existing business intelligence tools. All this is done at less than one-tenth the cost of traditional solutions.
Hadoop - the new enterprise data operating system With distributed analytics frameworks, companies can now execute a number of different data manipulations & analytic operations by plugging them into Hadoop as the distributed file storage system. The functionality of being able to perform different queries & data operations against data in Hadoop has made it an affordable, general purpose operating system where companies can put data meant for future analysis.
Big data lakes Rules of database management dictate that you must first design a data set before entering any data. The concept of big data lakes, also called enterprise data lake or enterprise data hub, totally nullifies that model. This emerging trend provides tools for database managers to analyze the data, along with a high-level definition of what data exists in the lake. Although the people who use this method of data entry must be highly skilled as big data lakes are one of the emerging trends in the world of data analytics.
Deep learning Based on neural networking, deep learning is a set of machine-learning techniques. It enables systems to pinpoint items of interest in large quantities of unorganised data. It helps to infer relationships between data entries without the need for specific programming instructions. For example, a deep learning algorithm on Wikipedia learnt on its own that California & Texas were both states in the United States of America. This principle of cognitive engagement and the things it implies are an important future trend in big data analytics.
More NoSQL Database managers are slowly turning away from traditional SQL-based relational databases towards NoSQL (Not Only SQL) databases for use in specific types of analytic applications. Although open source NoSQL database management systems have been around for a while, they have begun to gain momentum now because they provide the necessary tools to database managers to perform the kind of analyses they need.
Trained & skilled big data analysts are in demand for high profile, well paying job opportunities. The right course from the right academy is your first step towards a great career in big data & IT.
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