Discover real-time insights and forecasts from industry experts to stay ahead of the curve in 2023: business trends and predictions compiled for your informed understanding. Several key items made it into the concise and focused brief listing.
- As cloud computing continues to gain traction, streaming services are poised for widespread acceptance, with its scalability and cost-effectiveness serving as a catalyst.
- Real-time analytics infrastructure will progressively replace traditional batch-based architectures.
- Real-time streaming data should inform the bottom line of the business.
- Streaming real-time information unlocks new opportunities for machine learning, enabling applications such as traffic monitoring, supply chain optimization and financial market analysis.
Real-time streaming information has revolutionized the way we consume and interact with data, enabling instantaneous access to updates, insights, and trends.
Streaming information surged into the global spotlight in 2022, revolutionizing the way we consume content and entertainment. Confluent’s research reveals a staggering 97% of global corporations rely on real-time data streams, solidifying their significance within the ever-evolving information landscape. As the vast majority of businesses that leverage streaming data have observed, their annual income growth has surged by more than 10%, underscoring the profound impact that streaming data can have on a company’s bottom line.
According to Lenley Hansarling, Chief Product Officer at Aerospike, real-time streaming information is poised to gain traction in 2023, paving the way for its deployment in high-impact projects. Despite uncertainty surrounding the global economy, real-time data is poised to grow by over 30% in 2023 as businesses increasingly require accurate and comprehensive insights into their operations. Companies will capitalize on real-time insights to proactively neutralize risks and unearth additional value in their margins and operating expenses.
To effectively leverage streaming information within organizations demands a strategic investment in employee education and training. Stream processing was previously the domain of highly skilled “big data engineers,” requiring extensive experience in designing and managing complex, distributed systems. As technology advances, we anticipate that streaming information will become increasingly more accessible and user-friendly through educational and training programs, including cloud-native solutions, which will help bridge the gap to entry.
As Danica Effective, Senior Developer Advocate at Confluent, predicts, “The notion that data is a product will gain widespread acceptance in 2023.” Across various sectors, data flow has become increasingly integral to the operations and communication strategies of organizations within their own internal ecosystems. Despite the progress made, there remains a pressing need for widespread education on fundamental data principles and best practices, such as those articulated by data mesh, so that individuals can grasp these complex concepts. To facilitate seamless comprehension among creators, it’s essential to treat information as a consumable product, allowing diverse individuals to easily digest and utilize the knowledge without encountering significant barriers to entry. As data flows increasingly become the lifeblood of modern business, corporations will transition from simply leveraging information pipelines to harnessing these streams as a central nervous system, empowering more individuals to derive insightful decisions.
Transforming legacy batch-based architectures into real-time, event-driven systems that process and analyze streaming data in near real-time.
By integrating an event-driven streaming platform like Confluent Kafka or Amazon Kinesis with a batch-oriented data warehousing solution, you can effectively unlock the full value of your data within the organization. Transferring to real-time streaming enables the seamless integration of low-latency data across teams, unlocking opportunities for advanced analytics in areas such as anomaly detection, personalized experiences, logistics optimization, and more.
Eric Sammer, Decodable’s CEO, stresses the value of real-time data streams over batch-based systems in his 2023 forecast, underscoring how the latter can water down user expertise, saying: “As tech companies, our clients’ expectations have been shaped by their experiences with those apps. Legacy databases are ill-equipped to handle the technical realities of today’s world, and despite IT operations groups’ desire to emulate the sophisticated analytics stacks of top-tier corporations, delivering lightning-fast, up-to-the-second insights remains impractical due to time, skill, and cost constraints. Companies relying on batch ETL approaches for their data architecture risk losing customers to competitors offering a more personalized experience through a modern data stack that enables real-time, streaming analytics.
As we gaze ahead to 2023, it appears that corporations will be poised for significant change, abandoning outdated legacy systems for modern, real-time analytical architectures that can seamlessly process and manipulate data as it flows through intuitive stream processing capabilities. They will appreciate the benefits of straightforwardly addressing challenges such as data updates, complex joins, and continuous stream processing, while still accommodating both batch and real-time requirements seamlessly.
As companies shift from batch-based processing to real-time analytics, their data warehouses become less relevant, and instead, they focus on building systems that can efficiently handle continuous streams of data in modern formats.
As Jay Upchurch, EVP and CIO at SAS Software, notes, “By 2023, the trend will undoubtedly continue: organizations will progressively abandon traditional data warehousing for real-time database solutions that enable instant analysis and reaction to insights.” As organizations increasingly rely on processing information, they can transform complex data into actionable insights by storing it in user-friendly formats, making it easily accessible for reporting purposes – whether via denormalized files in a knowledge lake or key-value NoSQL databases such as DynamoDB. Whether monitoring streaming IoT data from equipment or retail traffic via ecommerce, real-time trend identification enables producers and retailers alike to proactively avoid costly mistakes and seize opportunities as they arise.
Actual-time streaming insights should directly impact the bottom line of the business.
Numerous organizations have heavily invested in their information infrastructures without being able to fully capitalize on the benefits in terms of revenue growth or operational efficiency. As the financial landscape evolves, every data repository and information system will come under intense pressure to deliver timely and actionable intelligence that directly impacts the bottom line?
According to Alexander Lovell, Head of Product at Fivetran, “2023 may indeed be a make-or-break year for data teams,” he notes. “Companies have continued to invest in IT despite significant variations in the quality of returns.” As market volatility intensifies, information providers must rise to the challenge, delivering actionable insights that mitigate the uncertainty caused by unreliable government guidance during times of economic turmoil. As the most influential clusters of information continue to evolve and grow in importance. Organizations lacking tangible insights will experience increased financial stress.
Knowledge and analytics will likely be a powerful software enabler of digital transformation. As organizations that have pioneered real-time streaming information continue to evolve, they are well-positioned to respond with agility, confidence, and intelligence as the financial landscape transforms. While being data-driven is crucial, organizations must also cultivate an adaptable infrastructure that facilitates continuous iteration and refinement. What drives developer velocity?
Despite numerous multi-year modernization efforts, many corporations have witnessed initiatives with long-term implications ultimately yielding little return within their initial timeframe. In 2023, it’s likely that every mission will need to demonstrate alignment with either cost savings or revenue generation, resulting in many long-term initiatives being condensed into projects with tangible impact.
The Year of the Information App?
Today’s world is all about apps. And we’re living in a time where people are getting more and more dependent on these little tools. But have you ever wondered what it would be like if an entire year was dedicated to just one app?
The greatest value you can extract from your data lies in feeding it back into your system to create engaging user experiences, combat spam, and inform operational decisions. Over the past decade, we’ve witnessed a surge in popularity of online apps and mobile apps. But as we enter 2023, it’s clear that this year belongs to the emergence of…
According to Dhruba Borthakur, co-founder and CTO of Rockset, dependable, high-performing data platforms will prove crucial in achieving success as businesses seek innovative ways to improve customer engagement and streamline internal operations. As seamless as ride-hailing and food delivery apps have become, the frustration is palpable when a request falls through due to technical glitches. Fuelled by cutting-edge real-time analytics, we anticipate a significant surge in demand for reliable and fault-tolerant data that is not only timely but also failsafe.
Each information app’s backbone will likely be a streaming architecture designed to facilitate effortless, instant experiences. While information apps were once limited to large online companies, by 2023, they will become integral components of both B2C and B2B organizations of all sizes.
Cloud-based infrastructure enables seamless real-time data streaming and processing.
As data streams in relentlessly, a constant flow of information never ceases to arrive. The appliance is always operational and running continuously for information purposes.
Due to the high costs of resources and the limitations of batch-processing architectures, real-time streaming data architectures have traditionally remained out of reach for many organizations. Real-time databases are sophisticated distributed systems that necessitate teams of expert information technologists to ensure seamless scalability and consistent performance at scale.
That’s all altering with the. At its foundation, the stack is anchored by cloud-native applications that can be architecturally designed to decouple storage and compute resources, enabling environmentally conscious scaling through more efficient utilization. These programs were designed to efficiently utilize resources and meet the rigorous demands of processing large volumes of streaming data.
Ravi Mayuram, CTO at Couchbase, believes cloud databases will revolutionize data management: “Cloud databases will achieve unprecedented levels of sophistication, empowering innovative applications in an era where speed, personalization, and immersion are the ultimate goals.” Implementing a reliable and scalable cloud-based data storage solution is a proven approach for achieving this goal. The rapid growth of serverless architecture and adoption of cloud databases is poised to revolutionize data management, ultimately becoming the standard solution for handling the information layer.
Moreover, databases will likely be evaluated increasingly based on their ability to ensure data quality, integrity, and security. Cloud-based data analytics providers will likely be scrutinized for their efficiency as companies seek to optimize their return on investment in a challenging economic climate, according to Dhruba Borthakur: “With the current market downturn, every business is under pressure to reassess the value of real-time information analytics solutions and make better-informed decisions about price-performance.” As competition intensifies among data providers like Snowflake and Databricks, companies showcasing their value to customers through benchmarking are emerging as clear winners, highlighting those info solutions that can achieve more with fewer resources. By 2023, a heated battle is expected to erupt among cloud computing providers, each touting their own eco-friendly infrastructure as the superior option.
Machine learning and real-time streaming information bring precision to your game.
Real-time analytics initiatives that yield significant impacts on revenue generation and operational efficiency are built upon intelligent foundations: leveraging anomalies, tailoring experiences through personalization, predicting estimated times of arrival, optimizing inventory management, and more.
Varun Ganapathi, co-founder and CTO at AKASA, believes AI’s impact parallels software’s in terms of deflationary pressures: “Microsoft CEO Satya Nadella recently remarked, ‘software is finally the most important deflationary force.’ I would take it a step further by saying that AI, among all software, poses the greatest deflationary pressure.” Deflation is primarily characterized by producing the same amount of output using significantly less currency, often achieved through the widespread adoption of automation and artificial intelligence (AI). By leveraging AI, businesses can automate tasks that consume significant amounts of human time and resources, replacing them with computerized processes at a fraction of the cost – leading to a substantial boost in productivity. As the corporate landscape faces ongoing financial challenges amidst market volatility, it’s likely that companies will need to consider implementing AI and automation initiatives to regain momentum, achieve cost savings, and drive productivity enhancements in the long run?
As traditional rule-based systems have long held sway, a new era is dawning where machine learning (ML) will empower numerous organizations to produce more accurate forecasts and respond swiftly to evolving circumstances. According to Anjan Kundavaram, Chief Product Officer at Exactly, “Profitable data-driven enterprises will need to tackle several critical AI and information science projects in 2023 to fully grasp the value of their data and realize a tangible return on investment.” These strategies encompass: (i) productizing data for actionable intelligence, (ii) integrating automation into core business processes to drive down costs, and (iii) elevating customer experiences through interactive platforms.
Real-time data streams are fundamental to machine learning applications. Dhruba Borthakur forecasts a surge in real-time machine learning: “As the sheer volume of real-time data continues to escalate, with constant updates and transformations, the need for real-time ML solutions is poised to skyrocket in 2023.” While batch prediction shortcomings are evident within individual expertise and engagement metrics for advice engines, they become even more pronounced in the context of online programs that detect fraud, as detecting fraud three hours later poses an extremely high risk for the business. Real-time machine learning (ML) is demonstrating a remarkable environmental benefit, with decreasing costs and operational simplicity driving its increasing sustainability. While some corporations remain divided on the value of online inference, pioneers in this space are reaping the rewards of their investment and leaving laggards in their wake.
The predictions preserve coming
Unfortunately, that’s all we had to go on for our 2023 real-time information forecasts. Below is an aggregated compilation of insights and forecasts from prominent online sources and thought leaders in the industry, providing valuable predictions for this blog.
