In this era of big data and analytics, the question which arises in most of the organizations is “Why big data capability framework is critical?”. The reasons would be simple, most of the organizations will have to address value and place bets to thrive in the market. Since technology is developing at an outstanding speed, the power of data and analytics also unfolds. This incredible growth is set to continue forward. If the organization chase after technology which does not align with the data requirement, there are high chances to burn the money. Big data framework enables the organization to move in a clear, prioritized and structured manner on how to make moves. The following are the ways in which big data analytics is helping organizations to drive significant growth.
Real-Time Solutions Expand
Most of the companies by now possess the technology to store and process the data. The real game changer is on the difference in how fast they can deliver analytics solution for a better decision-making. The speed processing capabilities of big data is increasing with the help of projects like Spark, Storm, Kafka etc.
Cloud Solutions Power Big Data Solutions
With the help of Internet of things (IoT), moving towards its pinnacle, data generation is on the increase. Hence applications involving IoT require a perfect scalable solution for managing the huge volume of data. Advantages of software on cloud is being realized by many organizations and is transforming towards coupling big data technologies and cloud.
The velocity quotient of data has improved tremendously. This motivated the users to perform more analytics on big data projects. Also, it encouraged the users to do more work with it. This benefits the organization, as the process is more oriented towards continuous analysis mode in contrast to weekly or monthly analyses.
Traditional Database Becomes Active
RDBMS systems have been dominating the database for a long time, structured data has been an integral part of the organization since then. Unstructured data from social media, IoT, are generating volumes of big data on a daily basis. From this, it is very lucid that unstructured data is increasing exponentially and there is a lot of untapped potential insights companies can get from these data.
Self-Service Data Applications Emerge
Data cleaning, data applications, data associative mining applications are upgrading continuously. Tools like Tableau with Hadoop are increasing their usage for the past few years. These tools help to reduce the efforts of end users. Firms like Informatica have already shown innovative frontline in this domain. It is very evident in the industries that other products and companies are working towards achieving it.
GPUs to Tackles the 3V’s of Big Data
Traditional software systems utilize only central processing unit architecture to keep in pace with the volume and velocity of data. As a result, IT departments require addition of more and more hardware to the system. This laggards the whole data pipeline and constrains the insights to be derived from the data. Graphics Processing Units (GPU) coupled with central processing units are the new solution to attain high-performance database engines and visual analytics. This new variant of GPU solutions is equipping the traditional software systems to move towards massive parallel processing.
Changing Roles in the Industry
As technology expands, data is moving across from the IT department. More teams within the organization are depending on analytical insights to arrive at a consensus decision. For example, data scientist role is slowly taking over the analyst role in data warehouse and business intelligence, which was traditionally focussed on statistics and machine learning. When data gets integrated with end to end platforms to improve the efficacy, the roles in the organization tend to fold and regress.