Data analysis has multiple facets and approaches
Published on : Wednesday 04-05-2022
Jasbir Singh, Automation Expert, Consultant & Implementation Strategist.
What exactly is Big Data? What actually is the difference between Big Data and Plain Data?
Data is mainly generated by the internet, through social networking, web search requests, text messages, media files, IoT devices and digital wireless sensors. The world continually generates nearly 2.5 quintillion bytes of data daily, in which the majority of the global data has been produced in the last couple of years only as per media reports. The exponential growth of data generated globally in the past one decade has caused worries to organisations about structured storage and meaningful use for analytics and future organisational benefits. The need of Big Data technologies arises, when the gathered data from multiple sources/systems could not stored systematically and processed manually or by traditional ways for future use. Many types of big data technologies are available for users to implement, which are linked to either of two major domains, operational and analytical.
What is the relationship between Big Data and Digital Transformation?
Big data technology is basically a software tool to store, analyse, and interpret the massive and large size structured and unstructured data. In the past, generated data was usually managed by programming languages. Due to continuous and exponential growth of the organisation's information, these programming languages were not efficient enough to handle the generated data in a structured format. Over the period it became important to have efficient technologies to handle such a huge amount of data in a structured way to meet the future need of the organisations.
Data has been compared variously to oil (black gold) and also garbage. How to make sense between the two extremes?
Data analysis is a process of inspecting, cleansing, transforming, and modelling data with the goal of discovering useful information, informing conclusions, and supporting decision-making. Data analysis has multiple facets and approaches, encompassing diverse techniques under a variety of names, and is used in different business, science, and social science domains. In today's business world, data analysis plays a role in making decisions more scientifically and helping businesses operate more effectively.
There are various tools and platforms claiming to provide the ideal fit for purpose. How should enterprises evaluate and select the right solution?
There are mainly two types of platforms for big data. One is Operational Big Data and the other one Analytical Big Data.
Operational big data technology mainly includes data that people use for process applications. In other words, it is online transactions, use of social media platforms, and the data generated by an organisation or a firm, required for the analysis by using the big data technologies software. The data collected as raw data is used as input by several Analytical Big Data Technologies. This includes online ticket booking systems, online trading or shopping from e-commerce websites, using online data on social media sites and daily data generated by the employees of organisations. Operational big data technologies include information from MNC management, Amazon, Flipkart, Walmart, and many more.
Big Data analytics is a technology that sees all aspects of business and derives the best way to make things work efficiently. It can optimise processes to get the best result out of it. Analytical big data technology is used when performance criteria have some target and rapid business decisions are required to be taken based on operational-real time data/information. Actual business decisions can be taken promptly with high accuracy. The common examples are stock market data, weather forecast based decisions, healthcare where the medical health of individuals can be monitored by doctors for prediction-based advice, and space mission data for microwave observations of storm’s precipitation, temperature, and humidity quickly in a short time.
Emerging Big Data Technologies
TensorFlow has comprehensive libraries, flexible ecosystem tools, and ecosystem of resources for researchers, supporting them to develop and deploy a unique Machine Learning application.
Apache Beam provides an API layout to build sophisticated Parallel Data Processing pipelines using various Execution Engines or Runners.
Docker is one of the tools developed to create Big Data management which makes the development, deployment and running of container applications easier.
Apache Airflow is a Process Management technology used for workflow automation and Scheduling for the management of data pipelines.
Kubernetes is one of the open-source Vendor-agnostic cluster and container management tools for Big Data
Whereas manufacturing companies and process industries have well defined benefit statements, how do service industries benefit from Big Data Analytics?
Big Data technologies are connected to Data storage, Data Science, Data Mining, Data Visualisation, Cloud computing, Data Analytics, Machine Learning, Deep Learning and on top of these are linked to Business Intelligence by handling large amounts of data from multiple sources. It provides a highly secured environment for numerous applications of Big Data management in sectors like banking, insurance, finance, medical, retail and many more.
How does the 5G rollout change the landscape of Digital Transformation?
The 5G networks rollout for fast and improved digital transformation in manufacturing and service sector by way of its speed of performance. Use of artificial intelligence (AI), the Internet of Things, cloud, and digital product/applications, 5G shall be the driving force behind the digital transformation in enterprises performance. 5G is seen to change socioeconomic infra of the world and every industry by the eruption of disrupting technologies to interconnect in the future. 5G technology is critical in the adoption of digital transformation strategy for improved digitalisation in the process to reap the benefits of cloud computing using artificial intelligence. Companies invest less time from planning to implementation by using 5G for reaching out to the market.
Jasbir Singh is an Automation Expert having long experience in Factory Automation, Line Automation, Implementation Strategist, Business Coach, Regular writer on automation, Artificial Intelligence, Robots/Cobots, Digital Technology, Network Communication, Industrial Internet of Things (IIoT), Wireless Communication, Block Chain and use of advance digital technologies. He has established a long association with Business Houses/large production houses to improve factory automation in their production lines as well as productivity improvement in factories in India and overseas; and in advising and designing the units to transform into digital platforms by use of Artificial Intelligence. Email: firstname.lastname@example.org
(The views expressed in interviews are personal, not necessarily of the organisations represented)