Top 10 Big Data Trends in 2023 You Can’t Afford to Ignore

Big Data is increasingly growing in scope in India, affecting the way industries function as well as boosting economies in its wake. Regardless of the size of an organisation, Big Data helps to make better organisational decisions and thereby brings order to the proceedings, making the world a more habitable place in its turn. Especially the transformations happened in Finance and Insurance Industry is tremendous.

At some point in the past, this was not the reality. Data was not always this “Big”. Only large-scale corporations had access to data then because only they could afford the technology that could process this data. In any case, their requirement was for a data analytics system that could take care of massive amounts of data, so they had hardly any choice in the matter.

Since that time, data has evolved at a terribly fast rate, allowing even smaller organisations to make use of the data they gather – all thanks to the internet and cloud technology. With big data cloud solutions, since they offer remote access to data using just the internet, there no longer remains any need for elaborate setups or data experts (who are not easy to acquire), thus saving these small organisations a fortune in internal spending.

The nuances that come with Big Data can now be handled just as easily by organisations that are intent on leveraging the value that it can bring. Moving beyond a simple IT Trend – as these things come and go, but mostly go, without being sustainable for development – Big Data has forged itself into the veins of the tech world, becoming one of its most prized assets.

And even as we write this, we are aware that Big Data is not one monolithic thing. It grows and changes to meet the demands of the various industries that it is a part of, seeking to solve its problems. 

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List of Exciting New Trends in Big Data

1. Quickly Growing IoT Networks

With the Internet of things (IoT), we find ourselves are the crossroads of extreme convenience at our fingertips. We can literally control the inside of our homes with this technology, and virtual assistants, like Microsoft’s Cortana and Siri are helping us navigate the true potential of these technologies.

One of the pillars of this kind of technology is data – since it is always on, there is a lot more potential to gather data. Thus, with the growth of the demand for virtual assistants, there will be a greater need for devices that can gather as well as process huge amounts of data.

2. More Approachable Artificial Intelligence

 Due to widespread industrial demand, Artificial Intelligence will be more commonly used to help organisations – both big and small – have more efficient business processes. AI can now execute tasks to a greater degree of competency than even some (or perhaps, most) humans.

Not only does this reduce the overall error rate, but it also improves the flow with which tasks are completed. This also creates a space for humans to perform tasks that uniquely leverage human intelligence as well, thereby proving to be an overall winner for any organisation, regardless of its size. At this point, the organisations that stand to gain the most are the ones that find the most efficient method of integrating these emerging AI technologies into their business processes.

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3. The Rise of Predictive Analytics

For a majority of its existence, big data has solely focussed on shedding light on events of the past – why certain things happened and how they can be understood within the context of a certain dataset. However, some part of it also concerns the future, and what is expected to happen, and this is called predictive analysis.

Predicting consumer behaviour takes companies one step closer to the source of the data as well as the desired subject of the data – the customer. For this reason, it goes without saying that this trend is likely to pick up in leaps and bounds in 2020, and is likely perhaps to be one of the biggest ways in which Big Data influences the daily livelihoods of everybody!

4. Cloud Migration of Dark Data

All the information in the world that has not yet been digitised is referred to as dark data, and it is highly likely that vast reserves of this data will be digitised in the years to come. Therefore, it is a trend that will be on the up without doubt, since they have huge untapped potentials for use in predictive analysis to aid businesses in their journey of growth.

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5. The Rise of Chief Data Officers

As data slowly and steadily starts to occupy a more and more central role in the functioning of organisations, chief data officers are surely headed on the rise. A CDO takes an active role in making sure that an organisation meets is data capabilities and does not lag behind. Thus, more and more people with a background in data will succeed in the years to come, since their keen insight into data, combined with industry experience, is likely make a huge impact on any organisation.

6. Quantum Computing

Although our technological advances have been immense, there are still many strides to take. One of them is quantum computing which, at least theoretically, has the ability to make huge data computations in a near insignificant amount of time.

To give a sense of the scope, even if a computer performs one data calculation that uses a billion data inputs every couple of minutes, that will be enough to give organisations a concrete sense of which direction in which to make decisions for better growth. It is only quantum computing that can facilitate this, and big tech companies like IBM, Microsoft, and Google all have quantum computers in their field of vision.

7. Smarter and Tighter Cybersecurity

Multiple organisations have been vulnerable to hacks and system breaches in the recent past. Moreover, given the constant-on nature of Internet of Things community, cybersecurity too is an issue of its own. For this reason, multiple organisations have got together to address this problem by integrating Big Data into an overall cybersecurity strategy. This trend is likely to continue well into the future, with companies preventing and mitigating future attacks and hacks purely through data information and security log data.

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8. Open Source Data

Increasingly, more open sources of data and data processing have been made available to the public. These open source solutions have made significant contributions in the field of data collection as well as data processing, and as a result of this, they are likely to be in high demand in 2020!

They mix the ease of use and availability of all good software with the reliability of both new and traditional softwares. Thus, it is inevitable that most companies – especially ones under a resource crunch – will try this method for their data uses.

9. Edge Computing

Hailed as another frontier in technology – yes, even the fourth industrial revolution has a new frontier – Edge computing is all set to make an industry standard. Due to the overall growth of IoT and of interconnected devices, there is an increased demand on gathering data from as many sources as possible.

This has resulted in demand for technologies which reduce the time delay between gathering data at a particular source and then uploading it to the cloud. Moreover, two further steps are also impacted: the analysis of this data as well as the action that needs to be taken as a consequence of the data gathered.

Given that it streamlines the data gathering and uploading process, edge computing delivers a much more efficient experience overall. Moreover, companies which make use of it can also make use of the benefits of storage by saving up on infrastructural cost – for this, they will have to delete any unnecessary data.

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10. Chatbots

Given that automated chatbots are all the new rage, they will are already being used to handle specific customer queries and provide a more personalised layer of interaction with customers. All this, while removing the need for human resources within the particular segment! The prediction is that chatbots will become even more significant in the days to come, thus further increasing the tech space’s dependence on chatbots.

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Thanks to Big Data, customers around the world – and across industries – are receiving more pleasant experiences. Since it enables companies to collect and process massive amounts of data, they are able to provide more accurate insights to customers, specific to their wants and needs. At the end of the day, it can play a significant role in increasing conversions.

If you are interested to know more about Big Data, check out our Advanced Certificate Programme in Big Data from IIIT Bangalore.

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What is Big Data?

Big Data is the process of studying enormous volumes of historical data in order to anticipate the future for researchers or businesses. It revolves around three concepts: volume, velocity, and variety so that any form of data is processed easily. Without employing typical data processing methods, Big Data handles both structured and unstructured data. It delivers information to everyone from the data processing streams. Big Data is mostly employed in research, analytics, medicine, education, and other areas where large amounts of data are handled. It was born out of social media, machine data, and transactional data.

How do different companies use Big Data?

Organisations utilise Big Data in their systems to enhance operations, provide better customer service, launch targeted marketing campaigns, and participate in other activities that boost long-term revenue and profitability. Businesses that use it correctly may have a competitive advantage over those that don't because they can make much better, faster decisions. Big Data is used by medical researchers and physicians to find illness indicators and risk factors, as well as identify diseases and medical issues in patients. In addition, information from electronic health records, social media platforms, the Internet, and other sources is merged to give medical industry and government entities real-time information on outbreaks of infectious diseases and epidemics.

How does Big Data work?

The working of Big Data consists of a few steps. First, the collected data in Big Data systems is left in its raw form and subsequently filtered and structured as needed for specific analytics purposes, or it is prepared for usage in applications using data mining tools and data preparation software. Since Big Data processing puts a lot of strain on the underlying computational infrastructure, external tools like Hadoop and the Spark processing engine are employed so that the clustered systems split processing workloads among many commodity servers. Large data sets are loaded onto external storage using these third-party solutions. Human-written queries are used to process the data. Lastly, these reports are used by the business intelligence team to decipher the predictive trend and correct earlier errors.

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