Striim’s 2019 Technology Predictions article was originally published on Forbes.
With 2018 out the door, it’s important to take a look at where we’ve been over these past twelve months before we embrace the possibilities of what’s ahead this year. It has been a 
fast-moving year in enterprise technology. Modern data management has been a primary objective for most enterprise companies in 2018, evidenced by the dramatic increase in cloud adoption, strategic mergers and acquisitions and the rise of artificial intelligence (AI) and other emerging technologies.
Continuing on from my predictions for 2018, let’s take out the crystal ball and imagine what could be happening technology-wise in 2016.
2019 Technology Predictions for Cloud
• The center of gravity for enterprise data centers will shift faster towards cloud as enterprise companies continue to expand their reliance on the cloud for more critical, high-value workloads, especially for cloud-bursting and analytics applications.
• Technologies that enable real-time data distribution between different cloud and on-premises systems will become increasingly important for almost all cloud use-cases.
• With the acquisition of Red Hat, IBM may not directly challenge the top providers but will play an essential role through the use of Red Hat technologies across these clouds, private clouds and on-premise data centers in increasingly hybrid models.
• Portable applications and serverless computing will accelerate the move to multi-cloud and hybrid models utilizing containers, Kubernetes, cloud and multi-cloud management, with more and more automation provided by a growing number of startups and established players.
• As more open-source technologies mature in the big data and analytics space, they will be turned into scalable managed cloud services, cannibalizing the revenue of commercial companies built to support them.
2019 Technology Predictions for Big Data
• Despite consolidation in the big data space, as evidenced by the Cloudera/Hortonworks merger, enterprise investment in big data infrastructure will wane as more companies move to the cloud for storage and analytics. (Full disclosure: Cloudera is a partner of Striim.)
• As 5G begins to make its way to market, data will be generated at even faster speeds, requiring enterprise companies to seriously consider modernizing their architecture to work natively with streaming data and in-memory processing.
• Lambda and Kappa architectures combining streaming and batch processing and analytics will continue to grow in popularity driven by technologies that can work with both real-time and long-term storage sources and targets. Such mixed-use architectures will be essential in driving machine learning operationalization.
• Data processing components of streaming and batch big data analytics will widely adopt variants of the SQL language to enable self-service processing and analytics by users that best know the data, rather than developers that use APIs.
• As more organizations operate in real time, fast, scalable SQL-based architectures like Snowflake and Apache Kudu will become more popular than traditional big data environments, driven by the need for continual up-to-date information.
2019 Technology Predictions for Machine Learning/Artificial Intelligence
• AI and machine learning will no longer be considered a specialty and will permeate business on a deeper level. By adopting centralized cross-functional AI departments, organizations will be able to produce, share and reuse AI models and solutions to realize rapid return on investment (ROI).
• The biggest benefits of AI will be achieved through integration of machine learning models with other essential new technologies. The convergence of AI with internet of things (IoT), blockchain and cloud investments will provide the greatest synergies with ground-breaking results.
• Data scientists will become part of DevOps in order to achieve rapid machine learning operationalization. Instead of being handed raw data, data scientists will move upstream and work with IT specialists to determine how to source, process and model data. This will enable models to be quickly integrated with real-time data flows, as well as continually evaluating, testing and updating models to ensure efficacy.
2019 Technology Predictions for Security
• The nature of threats will shift from many small actors to larger stronger, possibly state-sponsored adversaries, with industrial rather than consumer data being the target. The sophistication of these attacks will require more comprehensive real-time threat detection integrated with AI to adapt to ever-changing approaches.
• As more organizations move to cloud analytics, security and regulatory requirements will drastically increase the need for in-flight masking, obfuscation and encryption technologies, especially around PII and other sensitive information.
2019 Technology Predictions for IoT
• IoT, especially sensors coupled with location data, will undergo extreme growth, but will not be purchased directly by major enterprises. Instead, device makers and supporting real-time processing technologies will be combined by integrators using edge processing and cloud-based systems to provide complete IoT-based solutions across multiple industries.
• The increased variety of IoT devices, gateways and supporting technologies will lead to standardization efforts around protocols, data collection, formatting, canonical models and security requirements.
2019 Technology Predictions for Blockchain
• The adoption of blockchain-based digital ledger technologies will become more widespread, driven by easy-to-operate and manage cloud offerings in Amazon Web Services (AWS) and Azure. This will provide enterprises a way to rapidly prototype supply chain and digital contract implementations. (Full disclosure: AWS and Azure are partners of Striim.)
• Innovative new secure algorithms, coupled with computing power advances, will speed up the processing time of digital ledger transactions from seconds to milliseconds or microseconds in the next few years, enabling high-velocity streaming applications to work with blockchain.
Whether or not any of these 2019 technology predictions come to pass, we can be sure this year will bring a mix of steady movement towards enterprise modernization, continued investment in cloud, streaming architecture and machine learning, and a smattering of unexpected twists and new innovations that will enable enterprises to think — and act — nimbly.
Any thoughts or feedback on my 2019 technology predictions? Please share on Steve’s LinkedIn page: https://www.linkedin.com/in/stevewilkes/ For more information on Striim’s solutions in the areas Cloud, Big Data, Security and IoT, please visit our product page, or schedule a brief demo with one of our lead technologists.
