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Big data software will witness substantial changes to keep with the growing industry
BIG DATA TECHNOLOGIES- Big data is one of the most disruptive technologies of our time, that is shaping the industrial world. With data being everywhere, it’s useless for organizations without big data. By using big data technologies, organizations can gain insights and make better decisions that lead to greater ROI. To leverage this technology, the software is designed to analyze, process, and extract information from the heaps of unstructured data. Data professionals are familiar with Hadoop, Spark, NO-SQL, Hive, etc., but with so many advancements, it’s crucial to understand the future prospects of big data technology to evaluate which one is the right fit for an organization.
Breaking down Big data technologies
Big data technologies can be put in two classifications, operational Big data technologies, and analytical Big data technologies.
Operational Big data technologies predict the volume of data that is generated every day from online transactions, social media, or from a company’s software. This acts like raw data that supports the working of analytical big data technologies. Analytical technologies perform real analysis of all the data points for business insights, like stock marketing, weather forecasting, medical record analysis, etc.
Both these technologies are essential for efficient data management in this tech-driven world. To keep the momentum of developments going, many latest innovations are being done in the Big data environment. For better understanding, here’s an article that talks about the top Big data technologies and how they’re helping organizations get the best out of their data. But technologies are not the holy grail of Big data. Based on the demands and growth of the IT industries around the world, the future of Big data and its technologies will be shaped. According to industry experts, the following are the Big data technology trends to watch out for.
Upcoming Big Data Technology Trends
1. The Power of Cloud Solutions
AI and IoT are enabling faster data generation which is a benefit for businesses if they work wisely. Applications that are concerned with IoT will need scalable cloud-based solutions to manage the ever-growing volume of data. Hadoop on Cloud is already being adopted by many organizations and the rest should follow this lead to maintain their edge in the market.
2. A Big Shift within Traditional Databases
RDBMS systems were the preferred choices when structured data occupied the major portion of data production. But as the world is evolving, we are all producing unstructured data by using IoT, social media, sensors, etc. This is where NO-SQL databases come into action. This is already becoming a common choice in today’s business environments and the trend will only grow. NO-SQL databases like MongoDB and Cassandra will be adopted by more vendors and graph databases like Neo4j will see more attraction.
3. Hadoop will Stay with New Features
One of the most popular big data technologies, Hadoop, will come with advanced features to take on the enterprise-level lead. Right when Hadoop’s security projects like Sentry and Rhino will become stable, Hadoop will become flexible enough to work in more sectors and companies can leverage its capabilities without any security concerns.
4. Real-time Speed will Determine Performance
At this point, organizations have the data sources and the ability to store and process big data. The real factor that will determine their performance is going to be the speed at which they can deliver analytics solutions. The processing capabilities of big data technologies like Spark, Storm, Kafka, etc. are being fine-tuned with the speed in mind and companies will soon advance using this real-time feature.
