Big data analytics continues to impact every major industry, optimising industrial processes and finding more effective solutions for conventional business problems. As such, it enables experts to examine and assess a massive amount of information and study it for valuable insights and actionable patterns and trends.
With artificial intelligence, social media and other sources contributing to an excessive amount of new data that needs to be picked and analysed, data collection is nearly impossible using traditional methods. This is where big data analytics comes into the picture, increasing efficiency and reducing unchecked data backlogs. The sections below will examine how big data analytics saved the tech industry and why securing a position in this in-demand field is ideal!
Understanding big data analytics
Modern data is sourced from multiple channels. These channels range from sensors, mobile devices, media files, web information and social media, to name a few. This makes many traditional tools, like relational databases, redundant since they cannot properly gather, examine and manage the large data lakes transmitted from various sources all over the globe.
Big data analytics is the successful management system of data transmitted on a massive scale in several types and sizes that would not be utilised with traditional databases. The three V’s of this field are high variety, high volume and high velocity, as it is used for better prediction for business insights and gives organisations the ability to use improved business intelligence to make valuable decisions.
How is big data analytics influencing different industries?
Big data analytics helps businesses make improved decisions faster, allowing managers to develop effective strategies to maximise profit. The influence and benefits of these decisions are felt across different sections of the business, from higher management to operations management and the supply chain.
In a world where everyone with an electronic device is contributing data on the web, tools that can harness the excessive amounts of data being transmitted back and forth have become a necessity. Therefore, implementing systems that use the best combination of artificial intelligence, machine learning, and deep learning for data analysis is essential.
Modern businesses in 2023 will rely on complex big data analytics to provide insights for business operations. For example, they can use advanced predictive analytics to influence future consumer behaviour by analysing older data and combining it with statistics and data mining techniques. Other types of big data analytics include prescriptive, diagnostic and descriptive analytics.
If we look at the tool range used by a big data analyst, it includes tools like MongoDB, Talend, Cassandra, Spark and big data Hadoop. These tools integrate, store, distribute and study patterns that traditional systems could not identify earlier. They are a staple for multiple industries, including healthcare, entertainment and education, that constantly rely on them.
As the Information Age progresses and grows, big data analytics remains a field with endless potential and new opportunities, making it an excellent academic investment for first-timers and professionals willing to upskill. The following sections will examine how big data is used in different industries and in government.
Big data in healthcare
The healthcare industry has evolved over the past decade as technology continues to impact multiple medical decisions. Big data is a major driving force behind several successful changes that have optimised medical care quality for different consumer groups, predicted the strength of epidemics and identified ways to combat them. It also contributes insights that can result in increased profitability and contribute to the identification and removal of inefficient overheads.
Big data solutions and prescriptive analysis can scan massive amounts of data and transform them into valuable solutions that improve patient treatment options. On the other hand, doctors can use diagnostic analytics to identify early signs of a chronic illness in a patient so that it can be treated before it gets severe or life-threatening.
Big data in entertainment
Businesses in the media and entertainment industries have always focused on discerning consumer behaviour and market patterns in films, TV shows and games. Entertainment content is consumed through multiple electronic devices, such as laptops and mobile phones. As the variety of these channels grows, it results in an excessive overflow of incoming data that needs to be scanned and sorted before it is utilised in strategies.
By using big data analytics tools, organisations in the entertainment industry can keep pace with this evolution. They then construct an ideal web and mobile presence using the heavily processed data. Additionally, access to personal information allows for the development of new software tools tailored to individual preferences. Media companies can use modern tools like live streaming to connect directly with their audiences. These techniques utilise pre-scheduled media streaming and increase potential revenue.
Big data in government
The modern public sector is constantly overpowered by data emerging from countless technology sources, from satellites to CCTV cameras, sensors and social media (to name a few!). Big data analytics tools help process this data, and governments can use them to make quick and improved decisions.
When modern governments utilise efficient data mining methods, they can make valuable predictions about where the collected data could be used and maintain extensive databases that can replace paper records.
Since it is easier to store incoming data and skim through existing records, the coordination between different government departments increases. These changes promote better emergency responses in critical situations and limit fraudulent activities.
Big data in education
Big data is transforming the modern education sector. Whether it is people looking up courses on online platforms to study a new skill or students using software, such as Zoom or Photoshop, to get through their studies, big data’s influence is evident in the education sector. Online schools like the Institute of Data use big data analytics to adapt the applications and teaching channels they use in their courses in direct response to consumer feedback. However, it is equally helpful for other physical institutions as it can help to reduce costs and increase efficiency.
Educational companies can utilise big data analytics systems to process consumer data at an increased rate and provide effective solutions for teachers and students. Besides this, teachers can use big data to train each student according to their individual needs by offering personalised content. When big data is processed and implemented correctly, it helps educators design more effective solutions that encourage learners to be more enthusiastic about their selected program.
How is big data better than traditional data?
Unlike traditional data, big data can ensure real-time analytics for the gathered data. The use of big data can also improve customer relations, provide increased flexibility, reduce business costs, and help develop new, in-demand products and services. Moreover, with the apparent architectural differences, big data is far more scalable than its counterpart.
A few years back, traditional data needed to be collected before the analytics could occur. This meant that the final output and insights came to light long after the data was collected and were no longer relevant. However, big data makes the findings visible in real time and reflect fundamental changes, resulting in breakthroughs for multiple industries.
Improved customer relations
Social media monitoring is one of the most effective methods for collecting extensive data that defines consumer behaviour. This is extremely useful for organisations in the service industry, including but not limited to airlines and hotels. For instance, they can analyse negative social media posts regarding a customer’s experience, which helps them realise weak points and work towards improvements. Thus, consumer patterns tend to lean towards a more positive future output as customer relations improve.
To perform effectively, every business needs to be in sync with all the transmitted data, regardless of size, form or readability. It can be challenging to gather effective results when working with traditional databases, significantly hindering a business’s potential.
However, when it comes to big data, all information is stored in a raw format and is accessed through the dynamic schema. This system is not rigid and can perform multiple functions on the stored data, including managing, cleaning, analysing, visualising and ultimately transforming it into a properly structured, readable format.
Big data is ultimately more dynamic and can handle and process both structured and unstructured data. In contrast, a traditional database is static and inflexible, only able to immediately process data that fits its preconfigured relational structure base. Countless data forms cannot be utilised appropriately because of this system’s hindrances. The list includes web, text, geolocation, audio and video content information.
Big data helps businesses to identify more efficient methods of storing their information and carrying out operations in and beyond the workplace. Online cloud storage platforms, for instance, can keep and manage vast volumes of data that can be accessed remotely with just an internet connection. This can contribute towards cost reduction as the business no longer needs to invest in a separate database.
Innovative product development
Staying current with customer needs enables an organisation to plan it’s future better. This includes, but is not limited to, the product or service they must introduce in the market. The ability to attract new customers and solidify existing customer relations lies in innovating the right products, depending on what the people are looking for and when the time is right. Big data technology, therefore, allows businesses across the global industry to be more effective with their decisions.
Why is big data analytics the ideal route for you?
Big data analytics is an ideal route for you as it is an increasingly valuable skill set of modern technology. Organisations put their faith and procedure in the advancements brought through big data’s capability to identify and process all types and volumes of information for a more prosperous future.
As these new analytics systems slowly find their way into the more unique scopes of wide data, smart data, fact data and fast data, the overall field becomes more diverse and valuable. Furthermore, with new and improved tools, big data is used in all sorts of organisational advancements, from making accurate predictions and decisions to providing software for product innovation.
The skillset of taking data in different formats, assessing it and converting it into insights valuable for future business operations is in great demand. Some potential career roles include the options of being a big data consultant, data engineer and data scientist. Now would be an excellent time to invest in this booming tech field by cultivating a decision-making personality and honing your critical thinking skills.
Studying big data analytics will improve your skill set in any industry you choose, allowing you to maintain competitive leverage as a trained candidate with expertise in in-demand skills. See our data science programs if you want to open up to excellent employment options!