Sources of Big Data: Where does it come from?

  • Post category:General
  • Post author:
  • Post published:October 25, 2021
Source of Big Data

Addend Analytics is a Microsoft Gold Partner based in Mumbai, India, and a branch office in the U.S. Addend has successfully implemented 100+ Microsoft Power BI and Business Central projects for 100+ clients across sectors like Financial Services, Banking, Insurance, Retail, Sales, Manufacturing, Real estate, Logistics, and Healthcare in countries like the US, Europe, Switzerland, and Australia. Get a free consultation now by emailing us at or Contact us.

There has been a rising understanding of the role that Big Data can play in bringing priceless insights to a company, highlighting strengths and shortcomings, and helping businesses to improve their operations during the previous five years. Big data has no purpose, is non-judgmental, and apolitical; it simply shows a snapshot of activities.

Despite the fact that many businesses recognise the value of data, only a small percentage of them have seen its influence. According to a new report titled Broken Links: Why Analytics Haven’t Paid Off, while 70% of business leaders recognise the need of sales and marketing analytics, only 2% feel their analytics have had a broad, positive impact. This conclusion emphasises the importance of having Big Data managed by outsourced services who specialise in analysing data created by businesses and can provide actual, actionable insights. “Our survey and follow-up interviews with nearly 450 U.S.-based senior executives from industries including pharmaceuticals, medical devices, IT, financial services, telecoms, and travel and hospitality confirmed one thing that we already knew: few organisations have been able to get it right and generate the kind of business impact that they had hoped for,” Dan Wetherill writes in the foreword to his report.

So, what is Big Data and where does it come from?

The term is all-encompassing, and it refers to the massive amounts of data generated by businesses in today’s commercial climate. The 3Vs – the volume, velocity, and variety of data entering a system – have been the focus of big data gathering theory. For many years, this was sufficient, but as businesses shift their operations online, this definition has been modified to include variability — the increase in the range of values typical of a large data set — and value, which meets the need for enterprise data valuation.”

Big data analytics and AI with Azure Databricks

Play Video

The Sources of Big Data

Big data is mostly derived from three sources: social data, machine data, and transactional data. Furthermore, businesses must distinguish between data generated internally, that is, data that resides behind a company’s firewall, and data generated outside that must be imported into a system.

It’s also vital to consider if the data is unstructured or structured. Because unstructured data lacks a pre-defined data model, it necessitates additional resources to comprehend.



The three primary sources of Big Data

Social data

comes from the Likes, Tweets & Retweets, Comments, Video Uploads, and general media on the world’s most popular social media platforms. This type of data may be quite useful in marketing analytics because it provides essential insights into consumer behaviour and sentiment. Another good source of social data is the public web, and tools like Google Trends can help enhance the volume of big data.

Machine data

includes information generated by industrial machinery, sensors put in machinery, and even web logs that track user behaviour. As the internet of things becomes more prevalent and develops over the world, this type of data is predicted to grow rapidly. In the not-too-distant future, sensors such as medical gadgets, smart metres, road cameras, satellites, games, and the quickly expanding Internet of Things will give high velocity, value, volume, and variety of data.

Transactional data

is derived from all online and offline transactions that occur on a daily basis. Invoices, payment orders, storage records, and delivery receipts are all considered transactional data, but data on its own is nearly worthless, and most businesses struggle to make sense of the data they generate and how to use it effectively.

Unlocking real value from data

The capacity to combine this data in ways that generate insights, decisions, and actions is where real commercial value is created. Addend Analytics assists businesses in developing a complete, holistic, and long-term analytics strategy that provides them with the capabilities to differentiate themselves through actionable insights while also supporting employees and the business. A lot of things testify to the importance of the niche that Addend Analytics is filling. According to a recent survey, two-thirds of the organisations with the most advanced technologies in this field are unable to hire enough personnel to operate these capabilities. Furthermore, analytics consumes a lot of resources.

Large organisations struggle to assign enough resources, but smaller businesses are unlikely to be able to devote all of the resources required for effective analysis. Outsourcing is a tremendous asset in each of these situations.

While it is well recognised that big data can provide a competitive advantage, businesses who engage with skilled third-party providers have a much better chance of receiving high-quality, cost-effective insights. The era of big data has arrived, and the question is not about whether or not businesses should engage with it, but how. Cisco anticipates that by 2020, the amount of data created will be 50 times what it is today. It’s no surprise that businesses are feeling overwhelmed and in desperate need of sound guidance from experts who understand their industry and can combine it with technology to get results.

Being proactive is key

Advanced Analytics is displacing traditional reporting and business intelligence. It’s no longer enough to look back and try to figure out what went wrong. Instead, systems and partnerships must be established that take use of high-quality data and evaluate it to generate predictions about what will likely happen next, with real proof to back up the statements.

With Cloud-based Big Data as a Service, businesses can handle business demands across the whole range of analytics requirements, from data supply and management to data utilisation. They may create an insight framework and optimise the total value of enterprise data by developing a comprehensive cloud-based big data strategy. Cloud-based big data analytics, on the other hand, is not a one-size-fits-all solution, and a skilled IT partner like Addend Analytics can assist you along the way.