Learn the Big Data basics in 5 minutes!
What it is, the history, the trends and how it will impact you day to day
In the age of information overload, data is king.
The amount of digital data generated each day is mind-boggling, with estimates ranging from 2.5 quintillion bytes to 90 zettabytes.
As our world becomes increasingly digitised, data-driven insights are becoming more valuable than ever before. Big data, the term used to describe the massive datasets that are too complex for traditional data processing software to handle, is the driving force behind many of the world’s most innovative companies and groundbreaking scientific discoveries.
But what exactly is big data, and how does it differ from traditional data? How are companies and organisations leveraging big data to gain a competitive edge? And what are the ethical and societal implications of a world where data is more valuable than gold? In this blog post, we’ll dive deep into the world of big data, exploring its history, its potential, and its pitfalls. So grab a cup of coffee and join us on this journey into the heart of the data-driven world.
What is it?
Big data is a term used to describe the large volume of structured and unstructured data that is generated and collected by organisations on a daily basis. This data can come from a variety of sources, including social media, online transactions, and IoT devices.
The impact of big data on organisations is significant. They are now able to analyse vast amounts of data to gain insights into customer behaviour, market trends, and potential risks. This allows them to make more informed decisions, improve their products and services, and stay ahead of the competition.
Big data has had a significant impact on how organisations leverage Machine Learning. ML algorithms can be trained on large amounts of data to make predictions and automate decision-making. For example this can help financial institutions to identify potential fraud, improve their risk management, and make better investment decisions.
Overall, big data is having a major impact on all industries by enabling organisations to make better decisions, improve their operations, and stay ahead of the competition. As the volume of data continues to grow, it is likely that the use of big data and analytics will become even more important in the future.
The benefits of big data come with concerns for data privacy and security. Institutions must be vigilant in ensuring that they are protecting their customers’ personal data, and that they are complying with regulations such as GDPR and CCPA.
Big data is a powerful tool that can help financial institutions to gain valuable insights and make better decisions. As the volume of data continues to grow, it is likely that the use of big data and analytics will become increasingly important for financial services in the future. This is why it’s crucial for financial institutions to have the right data management and analytic tools to collect, store and analyse the data effectively and securely.
History
Big data technically refers to the collection, storage, and processing of extremely large and complex datasets that exceed the processing capabilities of traditional data processing systems. These datasets can come from various sources such as social media, IoT devices, and online transactions and can be structured, semi-structured, or unstructured.
The history of big data can be traced back to the early 2000s when internet companies such as Google and Yahoo began to collect and store large amounts of data generated by their users. At that time, the storage and processing of this data was done using traditional relational databases and data warehousing techniques. However, as the volume of data continued to grow, it became clear that these traditional systems were not capable of handling the scale and complexity of the data.
To address this challenge, new technologies and architectures were developed to enable the storage and processing of big data. One of the most significant innovations in this area was the development of the Hadoop framework, which allows for the distributed storage and processing of large datasets across a cluster of commodity hardware. This made it possible to store and process big data at a significantly lower cost than traditional data warehousing systems.
In addition to Hadoop, other big data technologies such as Apache Spark, Apache Kafka, and Apache Storm were developed to enable real-time data processing and streaming.
With the rise of big data, NoSQL databases such as MongoDB and Cassandra were also developed, which are designed to handle the scale and flexibility of unstructured data.
In recent years, big data has become a key driver of digital transformation across various industries. With the advent of artificial intelligence and machine learning, big data is now being used to develop predictive models and automate decision-making.
Today, big data technologies are being used by organisations of all sizes and across all industries to gain insights and make better decisions. It’s becoming increasingly important for companies to have the ability to collect, store and process large amounts of data in order to stay competitive in today’s fast-paced business environment.
So… What is next, what trends are we going to be seeing!
The trend of big data into the future is expected to continue to evolve and grow in several ways:
- Increased Volume and Variety of Data: This will be driven by the proliferation of IoT devices, social media, and other sources of data.
- Cloud-Based Big Data Solutions: More and more organisations will move their big data processing and storage to the cloud. This will enable them to take advantage of the scalability, cost-effectiveness, and flexibility of cloud-based big data solutions.
- Real-Time Processing: The need for real-time processing of big data will continue to grow. This will be driven by the increasing use of big data in areas such as fraud detection, risk management, and customer engagement.
- Artificial Intelligence and Machine Learning: The use of AI and machine learning will become increasingly important for big data analytics. These technologies will be used to uncover hidden insights, make predictions, and automate decision-making.
- IoT and Edge Computing: The growth of IoT will drive the need for edge computing, where data is processed at the source, rather than being sent to a central location for processing.
- Data Privacy and Security: With the increasing volume and sensitivity of data, organisations will need to focus on data privacy and security. This will include implementing measures to protect personal data and comply with regulations such as GDPR and CCPA.
What’s the impact on your day-to-day
Marketing
Imagine that you are a customer of a large retail store. You regularly shop at this store and use the store’s loyalty card to earn rewards and discounts. The store collects data on all of your purchases, including what you buy, when you buy it, and how much you spend.
One day, you receive an email from the store offering you a personalised coupon for 20% off your next purchase. You are surprised and pleased by the offer. Upon further inspection, you notice that the coupon is valid for a product that you have been considering buying for a while, but haven’t yet made the purchase.
You decide to take advantage of the offer and make the purchase. When you arrive at the store, you are greeted by an associate who greets you by name and hands you the coupon. The associate also mentions that the store has recently received new products similar to the one you purchased, and offers to show them to you.
You are impressed by the level of personalisation and attention that the store has provided. You realise that the store used big data to analyse your purchase history and preferences, and used that information to offer you a personalised coupon and shopping experience.
This is just one example of how big data can impact individuals in a positive way. This can be seen in many other areas of life, as well, such as healthcare, transportation, and entertainment. By analysing large amounts of data, organisations can gain insights and make decisions that can improve the lives of their customers and clients.
Health
Imagine you are a patient with a chronic disease and you are being treated by a healthcare provider. Your healthcare provider has access to a vast amount of data, including your medical history, lab results, and treatment plans. They also have access to data from other patients with similar conditions, which allows them to compare and contrast treatment plans and outcomes.
One day, your healthcare provider suggests a new treatment plan for you. They explain that the plan is tailored to your specific condition and is based on the data from other patients with similar conditions. They also explain that they have used big data analytics to identify patterns and trends in the data that indicate this new treatment plan will be effective for you.
You decide to follow the new treatment plan, and over the next few months, you notice a significant improvement in your condition. You are able to reduce your medication and have more energy.
In this case, big data has had a direct and positive impact on someone’s personal health. By analysing large amounts of data, healthcare providers can gain insights that can improve the care and treatment of their patients. This can lead to better health outcomes and a better quality of life for individuals.
It’s important to note that this example is fictional and not based on any specific case, but it illustrates how big data can be used in healthcare to improve patient outcomes.
Environment
Imagine you are a city resident who is concerned about air pollution. You have noticed that the air quality in your city is poor and you want to take action to reduce your exposure to pollution.
You decide to download an app that provides real-time air quality data for your city. The app uses data from sensors and other sources to provide information on the levels of different pollutants in the air, as well as the forecast for the next few days. You also use the app to find the nearest green spaces and parks, which have been shown to have better air quality.
You start using the app every day to plan your route to work and to decide when to go for a walk or run. You also use the app to report any incidents of pollution that you see, such as a factory releasing smoke. You also notice that the app has a feature that allows you to track your personal exposure to pollution over time, and it gives you recommendations on how to reduce your exposure.
You realise that the app is using big data to provide you with real-time information on air quality and to help you make informed decisions about your health and well-being. By using big data, the app is able to provide you with personalised recommendations and insights.
This example illustrates how big data can be used to improve the quality of life for individuals. By providing real-time information and personalised recommendations, big data can help people make better decisions about their health and well-being.
What Next
It is clear NLP will drastically impact all of our lives be it us directly interacting and leveraging the technology or organisations using these tools to provide new and improved services.
If you want to learn more I would recommend checking out;
- Youtube videos on the topic
Or learn about other technologies like;
