One significant trend in the field will involve the ongoing delegation of authority over analytics to entire workforces, rather than solely to data engineers and scientists. This will result in novel approaches to working, such as augmented working, which utilizes technology to provide useful insights for all individuals to use, enhancing their job performance and productivity.
By 2023, companies will realize that data holds the key to comprehending their customers, innovating better products and services, and optimizing their internal processes to decrease expenses and inefficiencies.
It is becoming more evident that the utilization of data-driven insights by non-technical personnel, including frontline employees, shop floor workers, marketing, and finance departments, is necessary for complete realization of its potential.
Data democracy in action can be seen through the utilization of natural language processing (NLP) tools by lawyers to sift through case law documents, as well as the use of hand terminals by retail sales assistants to access real-time customer purchase history and suggest appropriate products for up-selling and cross-selling purposes.
McKinsey’s research reveals that companies which grant their entire workforce access to data have a higher probability of describing analytics as having a beneficial effect on revenue, with a factor of 40.
The application of Artificial intelligence (AI) might possibly be the most influential technology trend that alters our way of life, employment, and business practices in the foreseeable future.
Data democratization, as mentioned earlier, will have a positive impact on business analytics by enhancing the precision of predictions, diminishing the time spent on menial tasks such as data acquisition and cleansing, and granting employees the ability to utilize data-driven insights irrespective of their job position or technical proficiency.
In basic terms, AI enables companies to swiftly analyze data and extract insights that would take significantly longer to obtain through manual efforts. Software algorithms employed by machine learning (ML), a type of AI currently utilized by businesses, progressively improve their performance with increasing data input.
Technologies such as NLP, computer vision, and generative AI fall under the scope of AI and ML. With NLP, computers are able to comprehend and interact with us using human languages. Computer vision, on the other hand, allows machines to interpret visual information from cameras in a manner similar to how our eyes work. Generative AI is capable of generating text, images, sounds, and video from scratch.
2. Services such as Cloud and Data are available as a Service.
In essence, this implies that via cloud services on a billing plan that involves payment for usage or subscription, companies can utilize data sources obtained and handled by third parties. This helps in minimizing the necessity of companies to establish their own costly, exclusive data collection and storage systems, which is applicable to a variety of applications.
Apart from providing raw data, DaaS firms also offer analytics tools as a service. Typically, the purpose of accessing data through DaaS is to enhance a company’s indigenous data collection and processing capabilities, resulting in more valuable and extensive insights.
This technology contributes significantly to the democratization of data mentioned earlier because it eliminates the need for businesses to establish and maintain costly and specialized data science operations to handle data. By 2023, the market value of this service is projected to reach $10.7 billion.
Data that is updated instantly, as it occurs, is known as real-time data.
The growing significance of real-time data for businesses lies in its ability to offer current insights as opposed to those from the past such as yesterday, last week or last month, when delving into data for meaningful revelations.
Dealing with data in real-time frequently entails a more complex data and analytics setup, resulting in higher costs, but the advantage is our capacity to take action based on current information.
One possible rephrased version could be: To achieve this, we might examine clickstream data collected from our website’s visitors to determine which offers and promotions to present to them. Similarly, in the financial sector, we would keep a close eye on transactions occurring across the globe to identify potential red flags that may indicate fraudulent activity.
Social media sites like Facebook analyze hundreds of gigabytes of data per second for various use cases, including serving up advertising and preventing the spread of fake news. And in South Africa’s Kruger National Park, a joint initiative between the WWF and ZSL analyzes video footage in real-time to alert law enforcement to the presence of poachers.
In order to gain a competitive advantage, more and more organizations are relying on data, which means that those with sophisticated data strategies will prioritize the most current and valuable data. Consequently, real-time data and analytics will be the most valuable big data tools for businesses by 2023.
4. Regulation and governance of data.
In 2023, there will be an increase in the implementation of regulations by various governments that aim to govern the utilization of personal data and other types of data, leading data governance to be a significant topic.
Following the lead of European GDPR, Canadian PIPEDA, and Chinese PIPL, it is highly probable that other countries will enforce laws safeguarding their citizens’ data. Gartner analysts have anticipated that by 2023, around 65% of the world’s inhabitants will be governed by regulations comparable to GDPR.
In the upcoming year, businesses worldwide will need to prioritize governance to guarantee that their internal methods for handling and processing data are sufficiently documented and comprehended.
Numerous enterprises will need to conduct audits to determine the specifics of the data they possess, the method of acquiring it, the location of storage, as well as its utilization. Although this might seem like additional labor, the ultimate goal is that individuals will have more confidence in organizations safeguarding their data, which will be advantageous for all parties in the future.
Afterwards, these organizations can utilize this data to create offerings that better correspond to our requirements at reasonable prices.
5. Business Intelligence
Business Intelligence (BI) uses software and services to deliver actionable information that provides its users with detailed conclusions about the state of their business. In the coming months and years, this discipline will continue to develop and reach all sectors. We will see its influence on both strategic and tactical business decisions.
It is predicted that the BI and analytics market will achieve a worth of 18 billion worldwide by 2025, leading to growth across the board. The implementation of Collaborative BI will enable non-expert users to access valuable information effortlessly, eliminating the necessity for specialized platforms.
6. Cloud Technology
At least some of the workloads of over 70% of businesses have been transferred to the cloud, and it is predicted that even more will adopt cloud technology in the future. A recent investigation by McKinsey revealed that enterprise spending on cloud computing went beyond the designated budget by 23%, and 30% of the expense was not effectively utilized.
The longevity of our business and IT structures hinges solely on cloud-native technologies because of their ever-changing nature. Nonetheless, their intricacy necessitates uniform self-service mechanisms that enable laymen to accumulate, scrutinize, and construe data.
7. Technology and Wellness
Data plays a crucial role in the prominent position of the health and wellness industry in our daily lives. Medical facilities are exploring novel methods to interact with patients, whilst organizations are focusing on devising and executing plans to enhance the well-being of their employees.
The capacity of corporations to gather medical information from all corners of the globe has increased, enabling them to discover remedies at accelerated rates. This phenomenon is likely to assist in the establishment of improved healthcare systems for individuals in the future.
8. Driverless Vehicles
Autonomous driving has been a topic of discussion for a while now, and it’s finally becoming more feasible. Waymo, Alphabet’s self-driving vehicle division, has already implemented autonomous cars in Phoenix and San Francisco. Additionally, Walmart has had an autonomous vehicle initiative in Arkansas since 2020.
Moving ahead is the only viable option for companies utilizing information gathered through initial trials of self-driving initiatives. Over the next few years, the utilization of large datasets will aid in establishing secure and competent methods of incorporating autonomous transportation into society, benefitting all individuals.
9. Big Data to Aid Climate Change Research
To achieve success in the battle against climate change, it is crucial that evidence-based discussions and measures are adopted. Supporting the forecasts made by climate organizations with reliable data will enable us to move beyond mere argumentation and collaborate on a global scale to execute the necessary actions in order to counter this peril.
Big data serves as a neutral information source that accurately depicts events occurring worldwide. With the aid of technologies like AI and analytics, it can identify the most efficient measures to facilitate collaborations between governments and enterprises.
10. Real-Time Analytics Gain Traction Post-Pandemic
In 2020, amid the covid outbreak, data aided not only in the quest for remedies and immunizations but also in regulating gatherings and upholding physical distancing measures.
For example, smart surveillance cameras can count how many people enter and leave a venue and alert once maximum capacity is reached. They can also be placed at key points that generate bottlenecks and detect times when the flow of people becomes too dense, making it difficult to maintain social distance.
Over time, data has been utilized to detect hotspots and contagious patterns, such as the presence of superspreaders, which has been a fascinating application. As we move past the phase of social distancing, we anticipate that these advancements will have a substantial impact on the growth of data science in general during the forthcoming months.
11. More Natural Language Processing (NLP)
The interaction between technology and people is being enhanced by big data, AI, machine learning, and the internet of things, with natural language processing (NLP) playing a significant role in humanizing these technologies.
With natural language processing, machines communicate on an equal level with humans, thereby reducing uncertainties and promoting the embrace of innovative technologies.
Intelligent systems will become more user-friendly with the help of NLP, enabling users to seamlessly communicate with them without a steep learning curve. This will facilitate the effortless integration of new technologies into their daily routine, making it a more organic experience.
12. Security Analysis with Big Data
Companies are naturally concerned due to the constant proliferation of digitalization which is causing traditional data security measures to fall behind, resulting in a surge of cybercrime and data security infringements.
Big data security analytics can prove to be highly beneficial in this particular scenario by enabling the swift accumulation, retention, and assessment of voluminous security data. Consequently, they aid in the identification and resolution of potential threats proficiently.
By utilizing big data in security analytics, it becomes feasible to handle enormous data sets and administer them in order to safeguard against cyber threats.
13. Robotic Process Automation (RPA)
RPA, which stands for Robotic Process Automation, is an advanced technology that enables the creation, deployment, and management of robots that imitate human behavior when interacting with digital systems and software.
One of the major benefits of RPA is its ability to complete significant amounts of tasks accurately and quickly, without any mistakes made by humans. We predict that it will become more popular among industries and businesses that prioritize precision and productivity. As a result, we consider it to be a significant trend in data and analytics for future years, including 2023.
14. Artificial Intelligence as a Service (or AIaaS)
AI as a service involves an external party providing sophisticated AI features in return for a recurring payment. This emerging phenomenon is particularly beneficial for small and medium-sized enterprises since it allows them to leverage the potency of AI without requiring in-house expertise.
AI as a service has a wide range of applications, such as customer service, data analytics, and production automation. It’s a readily available, economical, transparent, and expandable technology, making us confident that it has the potential to become a significant player in the realm of data and analytics.
Forecasting utilizing analytics
Predictive analytics, according to IBM, uses historical data, statistical modeling, data mining techniques, and machine learning to make predictions about future outcomes.
Predictive analytics will be crucial for businesses looking to detect hazards and chances, and devise fitting solutions, particularly in fields like climate, healthcare, or scientific inquiry, owing to the increasing prevalence of data.
16. Migration to the Cloud
The transfer of digital assets including data, workloads, IT resources or applications to cloud infrastructures is referred to as cloud migration, which involves a self-service environment and can be done on demand.
The advantages of cloud migration for enterprises are significant, as it allows for real-time efficiency and performance while minimizing uncertainty. As a result of these benefits, an increasing number of companies will transfer their digital assets to the cloud in order to enhance profitability, agility, and innovation in their business operations.
