2 Dec 2022| OES
The Key Technologies for Big Data Analysis
We have been experiencing how social applications are being built rapidly. People are being connected on social networking platforms sharing their opinions, pictures and videos. Consequently, there is a massive increase of data. However, businesses are able to use it more effectively to turn more competitive.
What is big data?
Big data refers to the vast data produced by Social media platforms, IoT devices, etc. Traditional databases cannot maintain such a massive amount of data.
Big data is a huge asset to any organization as it helps derive valuable insights concerning business growth. It serves businesses to refine the existing marketing campaigns and methods. Businesses can use the data efficiently to train machines to analyze the essentials.
Why do you need Big data?
Big data is being considered extremely important by more than 90% of organizations. Let us look below to know the key ways it helps business operations to function:
Leading technologies enabling big data analytics:
Predictive analysis helps businesses make effective decisions and cautions about any threats. Thus, big data plays a pivotal role in effectively assessing, understanding, and generating solutions.
Tools play a major role in identifying structured and unstructured data stored across various sources, and these sources could either be APIs, DBMS, etc. With the help of the tools, data can be segregated and used for one’s benefit accordingly.
Usually, data is stored across multiple platforms in various formats. The software is highly advantageous for choosing the most applicable data, collecting them, and further analyzing the information for the organization’s benefit.
Such analytics role is also vital to connect to the external data sources and make it a part of application flow.
Distribute data :
In-memory data fabric is vital, for this technology helps distribute large amounts of data across solid-state storage devices, dynamic ram and flash storage.
Distributed storage enables storing replicated data. Such provision helps to face node failure or any corruption in the significant data sources.
Integrating data :
Processing terabytes of data is a challenging role for any business. They need to do it to meet customer requirements. Some of the big data solutions can be named as follows;
Hadoop, Apache Spark, MongoDB, Amazon, EMR, etc.
Data is manipulated into a format that can be used for future analysis. The data sharing process is accelerated through unstructured data set formatting. Every task related to data processing cannot be automated. Humans have to oversee tasks that can be time-consuming and tedious.
Data quality is a prominent factor for processing data. Data quality software plays a pivotal role to enrich large data sets through parallel processing. This software generates reliable and consistent outputs.
All these technologies play a vital role in improving systems’ overall efficiency and making very informed decisions. It has a huge role to play across significant business domains.
What if employees are unaware of the big data technology? The results generated would not be up to the mark. So lies the need to train the employees with big data technology. Businesses that have adopted the technology will indeed derive optimal benefits.
How about AI technology proving its mark in handling big data. ONPASSIVE is an AI-driven organization with a handful of AI products to explore. O-Net, a refined social networking platform, will enable social and business communication to be more friendly. Optimize its usage to establish social connections and provide scope for generating quality data.
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Tags: Technology Artificial Intelligence