Last year marked a pivotal moment as generative AI captured the spotlight, demonstrating its potential across various industries. Looking ahead to 2024, we anticipate not just a continuation, but a significant maturation of this technology, with broader acceptance and innovative applications emerging across diverse sectors. This evolution will unlock new possibilities and redefine what’s possible, positioning AI holistically (not only Generative AI) as a cornerstone of technological advancement in the year ahead.
This leads us to take a closer look at three areas that our technologists feel will benefit from this continuing momentum and begin to yield results for organizations:
1) Increasing integration of AI toolsets within cloud and SaaS ecosystems
2) AI’s increasing contributions to executive decision-making
3) Platform Engineering’s continued emergence
2024 Tech Trends: AI Integration into Existing Ecosystems
First up is the convergence of data platforms, analytics, and AI toolsets within cloud and SaaS ecosystems. This was most prominently seen with the introduction of Microsoft’s Fabric Platform in 2023. As one of the market leaders, Fabric represents a strategic integration of Microsoft’s tech offerings, aimed at streamlining the data lifecycle from storage to insight.
RevGen Architect Andy Vold echoed this sentiment, “Tool consolidation under a single platform like Azure Fabric will increase speed of delivery and allow for easier flexibility to pivot or alter development direction as needed without major rework or new technology installations and integrations.”
Indeed, through Fabric, Microsoft combines many of the data and analytics tools that organizations need into one unified SaaS, including Azure Data Factory, Azure Synapse Analytics, and Power BI. Fabric is infused with Azure OpenAI, allowing you to build your own copilot and generative AI applications. Here’s a closer look at the key components and their roles within this ecosystem:
OneLake: OneLake is a SaaS, multi-cloud data lake that’s automatically integrated with every Fabric tenant, akin to how Microsoft 365 applications are connected to OneDrive. OneLake organizes and indexes data for ease of discovery, sharing, governance, and compliance, addressing the issue of data silos by providing a unified storage system for all developers.
Azure Data Factory: At the data processing layer, Azure Data Factory’s latest iteration enables efficient and advanced ELT (Extract, Load, Transform) processes. It acts as a modern data pipeline, facilitating the movement and transformation of data across various sources, preparing it for more complex analysis and applications.
Synapse Suite: This suite of tools encompasses a range of innovative data services, each tailored to specific needs within the data landscape. Synapse Data Engineering provides an enhanced authoring experience for Spark, coupled with the convenience of instant start capabilities in live pools and collaborative features.
Other Synapse tools include Synapse Data Science: offering a comprehensive end-to-end workflow; Synapse Data Warehousing, which merges the benefits of a lake house and a data warehouse, delivering unparalleled SQL performance on open data formats; Synapse Real-Time Analytics, which caters to developers handling data streams from IoT devices, telemetry, logs, and more. Together, these services provide a robust and versatile framework, addressing a wide array of data engineering, science, warehousing, and real-time analytical requirements.
Power BI: On the analytics and visualization front, Power BI is integrated to provide robust business intelligence capabilities. Enhanced with AI features such as natural language processing (NLP), natural language query (NLQ), and narrative generation AI, Power BI enables users to generate insights through more intuitive, conversational interactions with data.
Additionally, with Copilot in Microsoft Fabric, in every data experience, users can use conversational language to create dataflows and data pipelines, generate code and entire functions, build machine learning models, or visualize results.
Each of these components, while powerful individually, gains additional strength and utility through integration in the Fabric platform.
Technologist Andy Vold continued, “On top of this new convenience, the continued incorporation of AI into these tools I feel will eventually automate many tasks to the point where development becomes only a series of prompts to inform the tool what you need done.
“The speed of delivery could easily be cut in half allowing for much faster insights and time to work on additional initiatives that today’s development world doesn’t leave time for.”
Therein lies the true value of these innovations for organizations. In the coming year, we see wider use and adoption of cohesive ecosystems like Fabric, ushering in a new era in business data management, AI, and analytics, which promises to revolutionize the way organizations harness their data.
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This brings us to our second theme – that of enhanced decision-making capabilities for leadership. As Anne Lifton, Principal Architect of AI and Advanced Analytics states, “In 2024, I believe we will start to see some changes in how data drives executive decision making. In the past, we generated a myriad of reports to give leadership access to as many business metrics as possible, we have come to realize that simply making more reports can create noise and decision fatigue.”
One McKinsey study indicated that only 20 percent of respondents feel their organizations excel at decision-making. This is despite continued investment in business intelligence by organizations – with some estimates putting the BI market in 2023 at over $29B. Lifton continued “I believe AI and advanced analytics will be used to help identify critical trends that might be simply lost in the noise of the normal deviations of business cycles.”
Unified offerings like Azure Fabric, AWS Glue, and GCP Dataflo will play an important role in simplifying and making advanced analytics more accessible for businesses, paving the way for more agile decision-making. By organizing large volumes of structured and unstructured data, we couple these platform data tools with generative AI, which can process extensive amounts of data, comprehend complex ideas, discern intricate relationships, and produce insights at a scale and speed far beyond what humans can.
With the integration of these advanced AI functionalities, businesses are more effectively positioned to link their data, metrics, strategic planning, and operational tasks, leading to enhanced overall efficiency. It can automatically discern trends, capture complex emerging concepts, and summarize huge volumes of data efficiently, giving business leaders the ability to connect data to results much more quickly.
2024 Tech Trends: Platform Engineering
The third theme has a significant potential to reshape the software engineering landscape in the coming years: Platform Engineering. At its core, Platform Engineering involves the creation and management of self-service platforms for software development teams. These platforms are designed to provide standardized, easy-to-use tools and services that streamline the development and deployment process, reducing the operational complexities often associated with software engineering.
As RevGen Principal Architect Kevin Able explains, “Platform engineering empowers developers by abstracting away infrastructure complexities, providing standardized tools, and automating repetitive tasks. By streamlining development workflows and reducing operational overhead, platform engineering enables developers to focus more on coding and innovation, ultimately leading to increased productivity and faster time-to-market for software products.”
The benefit of Platform Engineering lies in its ability to bridge the gap between development and operations, enabling developers to focus on coding while the platform handles the intricacies of the infrastructure. This approach not only accelerates the software development cycle but also enhances the quality and reliability of the software produced. Automated deployment processes play a pivotal role in this, streamlining the release process, reducing manual errors, and ensuring consistent and predictable deployments.
By leveraging Infrastructure as Code (IaC) tools like Azure Resource Manager (ARM) templates, Terraform or AWS CloudFormation, Platform Engineering teams can codify infrastructure configurations on cloud platforms, making them version-controlled and reproducible. This ensures that development, testing, and production environments remain consistent, reducing deployment errors and improving overall reliability.
Azure DevOps provides a comprehensive suite of tools for automating the software delivery process, AWS offers a similar solution through AWS CodePipeline. Through automated build process and deployment pipelines, teams can create and manage build, test, and deployment workflows, ensuring consistent and reliable deployments across different stages of the development lifecycle. These integrations seamlessly facilitate development on cloud infrastructure.
By automating and standardizing the development environment, businesses can achieve greater efficiency, reduce the time-to-market for new products, and foster innovation. Looking forward, Gartner predicts that by 2026, 80% of large software engineering organizations will establish platform engineering teams.
This shift underscores the growing recognition of Platform Engineering as a critical factor in achieving operational excellence and competitive advantage. As more businesses embrace this model, we can expect to see a significant transformation in how software engineering is conducted, with a stronger focus on efficiency, scalability, and innovation.
2024: A Year of Innovation
In 2024, the tech landscape is brimming with promising prospects, and RevGen Partners, with its skilled team, is uniquely equipped to help organizations capitalize on these cutting-edge technologies for strategic gains.
To understand more about our role in driving success via technological innovation visit our Technology Services page. To explore our approach to maximizing AI’s capabilities, we invite you to visit our AI page or contact us to speak to one of our experts.
Luis Martinez is a Manager at RevGen, specializing in identifying business improvement opportunities and their impacts on the Customer and Employee experience. He is passionate about empowering our clients to navigate challenges and enabling change.
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