Updated: Dec 30, 2022
Big Data, Small Data, or Data Analysis has carved a niche for itself in many professional sectors until it has become a fundamental tool in our day to day. But do we really know how to face all the challenges that Big Data and data analysis entail?
The year 2022 has been the year of the consolidation of the data scientist and data analyst profiles, two profiles that aim to obtain the maximum performance from the data to generate a positive impact in any type of organization. Both profiles share objectives but from different approaches, the data scientist to clean and filter the data, and the data analytics extract information from the data related to the business. The work of both and the support of management are essential to become a true Data Driven company. For all this, in this article, we point out the Big Data trends for 2023 so that you do not miss a detail. Do not miss it!
Big Data and Analytics Trends 2023
Before beginning, I want to highlight a phrase from the Director of IoT and Digital Transformation at Cisco Spain, Antonio Conde, to understand the magnitude of value that Big Data possesses: "Data is 'the new oil', they are becoming a key part of society and the economy”.
This is so because data is the new value to be managed by organizations of all kinds. Companies are looking for capacities in terms of data capture, storage, and processing, and those that achieve it will have achieved an advantage over their competition, which is called the Analytical Advantage. Those companies that achieve the long-awaited analytical advantages will be able to say, then yes, that they are true Data Driven companies, companies focused on the value of data.
1. Data Strategy: the data strategy integrated into the growth strategy of companies
If until now the data strategy was formulated independently by the IT or Data teams within the organizations and created to add to the global strategy of the companies, the course seems to have changed, and companies are already introducing data projects. data in its primary strategies forming part of the core business.
Therefore, in 2023 and beyond we will see the strategic plans of many organizations include clear elements of Data Strategy. In fact, we have to add that the vast majority of companies' digital transformation strategies are based on a data strategy. One more sign that it is one of the key trends of Big Data.
2. Artificial intelligence, the key to decision making
Another keyword when we talk about technological advances is AI, which is making it possible to be faster and more precise when making strategic decisions in many business sectors. What we will certainly see is how the rise of digital technologies, lower-cost data storage, high-performance hardware, and embedded software will spur change in businesses large and small alike.
Companies that adopt artificial intelligence as part of their business processes will be more and more. It is logical, since the advantages offered by this technology are many at different levels, such as, for example, at the level of processes, the creation of new business models, interaction with the client, and even interaction between the people of a company.
3. Data as a service and Cloud
Data as a Service uses cloud technology to give users and applications access to information on demand without depending on where the users or applications may be. It is one of the current Big Data trends.
In-memory computing is data being stored in a new level of memory that is situated between NAND flash memory and dynamic random access memory. This provides much faster memory that can support high-performance workloads for advanced data analytics in enterprises.
4. Democratization of data
One of the most important trends of 2023 in relation to Big Data will be the empowerment of all the human capital of the company, in relation to data analysis and its management, not only by Data Scientists or Big Data experts.
In addition, new data-based intelligent tools and applications are emerging to make data management more accessible and for any employee to do their job efficiently.
In fact, a study by McKinsey found that companies that make their data accessible to their entire team are 40 times more likely to make the right decisions regarding company revenue.
5. Big Data and climate change
Climate change may not be a new topic for scientists, but harnessing Big Data to combat it may be mainstream by 2023. In fact, it is believed that harnessing Big Data can help us understand the current state of climate change. carbon dioxide emissions. Not only that, but even data from meteorological research, earth sciences, ocean research, and even nuclear research facilities are stipulated to help us understand climate change and other environmental conditions related to the planet.
6. Natural language processing (NLP) and conversational analysis.
Just as search interfaces like Google made the Internet accessible to everyday consumers, NLP provides an easier way to ask questions about data and get more accurate information. Conversation analytics takes the concept of NLP a step further by allowing such questions to be asked and answered verbally rather than via text.
Another Big Data trend by 2023 will reportedly be NLP and conversational analytics driving BI and analytics adoption from 35% of employees to over 50%, including new classes of users.
The voice seems to be able to prevail as the main channel of interaction between machines and people, and in a way it makes perfect sense. Technology must be transparent to people in its use, and therefore, it must be natural. What is more natural than using the voice to communicate? This technology is in very immature phases but it is only a matter of time.
7. Connected data platforms
"The trend is towards the interconnection of data platforms within an ecosystem that allows adding greater value to the customer experience as a whole, and not in isolation," he adds. This trend, which already existed in previous years, is expected to be strengthened by 2023 thanks to the use of Cloud Computing. This will allow the development of advanced analytical actions with lower costs. Big tech companies like Amazon, Google, and Microsoft are investing heavily in their cloud platforms to enable this type of advanced computing on data.
8. Active Intelligence
Another trend in Big Data is Active Intelligence. The current processes that companies have to migrate data from their different sources to the catalog continues to be a great challenge for organizations, Parada tells us.
Companies that aim to be Data-Driven, and that have gone through the first phases of data collection and transformation, must continue their evolution toward Active Intelligence processes. In other words, the trend is towards the automation of the data path, from its source to Data Like”, he assures.
9. Legislation and protection
During the year 2021, the different government administrations took the reins to order and create the appropriate legislation regarding data analytics in particular, and artificial intelligence in general. Thus, Europe developed a new regulation on AI. This guarantees the safety of people and strengthens the investment in a humanistic AI. The objective is to find a balance between the fundamental rights of people and innovation.
At a geostrategic level, Europe seeks its independence from the hegemony that China and the US maintain over this technology. It cannot be forgotten that Europe has great assets such as its fiber connection network and 5G, its algorithms, and its industry 4.0, among others.
In this sense, by 2023 greater depth and detail are expected in the different European regulations that can be transposed by the different member countries of the European Union, which serve as protection against the large platforms and technology companies of China and the US.
10. Metaverse and data analytics
The metaverse could not be missing from the list of Big Data trends. The commitment of Meta, formerly Facebook, to the creation of a metaverse as a digital space for human interaction, creates a world of new opportunities for data analytics. If until now the geolocation of a person can only be done with the authorization of a judge, in the metaverse there would be no such restriction. This opens a new line of analysis of geolocated data in metaverses.
The negative part of this new opportunity for behavioral analysis will once again be who will be able to carry out these types of actions. Doubts also arise about the objectives and whether the user could refuse to have their browsing data used in the metaverse.