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What this blog covers:

  • In the changing digital environments, staying on top of data and analytics trends is essential for businesses.
  • Explore 5 top trends that will rule the cloud data and analytics industry in 2023 and beyond.
  • Learn how Kyvos can help organizations leverage these trends to push their data efforts in the right direction.
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The year 2022 firmly established that data is the new fuel for organizations moving toward complete digital transformation. We are, in fact, in an era of data power play where the paradigm has shifted to higher data literacy, and insights-savvy enterprises are taking the winning shots.

A completely data-driven business model now incorporates unified truth across the board in a well-managed and protected cloud environment. With global cloud spending predicted to reach around $600 billion by 2023, this comes as no surprise.

Moreover, in this changing world order, only those organizations can sustain and thrive that will leverage data in its fine-grained format at every level of operations. Data leaders are optimistic about the higher business impact of this cultural revolution and pushing the envelope to embrace new trends emerging in the market for 2023 and beyond. Some of these trends to watch out for are:

#1 Speed That Enables Real-Time Analytics Will Become Non-Negotiable

Instant data access is critical to make faster and better-informed decisions. Organizations can no longer rely on delayed refreshes of their BI dashboards when they need in-the-moment answers to critical queries.

Taking hours to track key metrics can result in losing millions of dollars or potential customers. What if your infrastructure took 5 hours to compute the number of users leaving your app due to a bug when you could’ve gathered the same information immediately in a few seconds? Imagine a bank missing the warning signs of a wire fraud scheme or a credit card scam due to a delay in monitoring daily transactions. It may lead to a loss of trust from customers or, even worse, penal actions from respective authorities.

As a business leader, the ability to anticipate future events, forecast needs, and make crucial decisions quickly is essential. Therefore, timely insights gained through instant and interactive analytics will become the table stakes, and adopting a cloud-based platform to achieve these results will be a no-brainer in 2023.

#2 Data Mesh Architecture Will Get Bigger

Data is growing exponentially every year, presenting both opportunities and challenges for businesses. However, this growth has also led to complexities such as data siloes, internal and external security threats, and fragmented reporting. Since data is mostly distributed across organizations, a transformation of architectural structures was warranted. That’s why the concepts of data mesh and data fabrics were adopted for better data management.

Data fabric comprises a stack of innovative technologies, while data mesh refers to a process where distributed teams leverage self-service analytics to use data according to their changing needs. Together, they can ensure better data governance and democratization for every user within an organization.

Though they have been around for a few years, these frameworks will gain more acceptance in 2023 and might take over the monolithic data warehouses. Nonetheless, more data leaders will use data mesh for deeper analytics, especially in federated working models, in the coming years.

#3 Data Democratization Will Enable a Single Source of Truth

As data-driven strategies are taking center stage for organizations, the need for a single version of the truth accessible to all business users is more important than ever. This reality has been accepted by around 79% of organizations in a recent survey.

Analysts often create their own version of metrics within the BI tools they use due to inherent business logic. However, they need to invest in an ecosystem that allows faster adoption of a universal semantic layer accessible via any analytical tool deployed within the enterprise.

By adopting this approach, businesses can achieve a 360-degree view of enterprise data for faster decision-making and empower their teams with all the data they need. But the success of this approach hinges on complete data democratization and literacy within the company. According to McKinsey research, organizations making data accessible to every employee are 40 times more likely to see positive results from their analytics.

Business users should learn to read and use data for their day-to-day operations. This is important because context-driven analytics will replace 60% of traditional analytical models by 2025. If your workforce fails to use data to its full potential with accurate interpretation, losses will be substantial. In 2023, businesses will need to prioritize the adoption of tools and technologies that can provide a unified view of their data to enable better decision-making across the organization.

#4 Focus on Cloud Cost Optimization Amid Global Economic Slowdowns

According to IMF reports, the global growth rate may be down to 2.7% in 2023. This economic slowdown has made enterprises re-evaluate their business intelligence (BI) and data analytics strategy.

To combat recessionary circumstances, companies are turning to deeper analytics to understand their current situation and make better decisions for the future, leveraging data as their secret weapon. Through timely analysis, they can identify areas to save money and make operations more efficient. For example, users can track customer spending patterns and find ways to cut costs without wasting resources.

While self-service data access is crucial for efficient operations, it can also lead to increased cloud consumption and subsequent cost explosions if not managed properly. This is especially true when it comes to analyzing cloud-scale data over and over again for critical business decisions, as each query can incur significant costs.

To manage costs while still providing self-service data access to users, enterprises should invest in an advanced BI ecosystem. This can include tools and technologies for monitoring and optimizing cloud usage, as well as automating common data processing tasks. By doing so, cloud resources will be used efficiently and cost-effectively without sacrificing the agility and flexibility enabled by self-serve capabilities.

#5 Data Security to Take Precedence with Growing Cloud Adoption

A Gartner report says that over 50% of companies will move to enterprise cloud platforms by 2027 to speed up their operational efficiency. With so much cloud exposure, CIOs must optimize their data resilience with enhanced digital immunity.

Data security can’t be an afterthought, and organizations must ensure safety at every step when handling sensitive data for business intelligence and analytics.

To ensure secure information transfers within the enterprise, robust security protocols like single sign-on, multi-level authentication, and role-based access controls will become imperative. CIOs will need to prioritize data security and invest in advanced security measures to safeguard their critical data assets. By doing so, they can enable their teams to extract valuable insights from their data while minimizing the risk of data breaches and other security threats.

Looking Ahead

Multi-cloud infrastructure adoption is on the rise, with about 90% of large organizations investing in it. However, smaller companies are often deterred by the high costs associated with this approach. Nevertheless, global cloud infrastructure spending is expected to surpass $118 billion by 2025-26.

Much of this expenditure will go to cloud-native applications, platforms, and solutions that will help businesses realize their potential and grow revenues.

Kyvos is the world’s fastest cloud BI Acceleration platform designed to provide enterprises with deeper insights and sub-second responses even from massive datasets. Our Modern OLAP technology enables-

  • Smart aggregation of queries for real-time insights
  • Load-based elasticity to optimize cloud costs
  • Multi-layered security for a secure BI infrastructure
  • Smart Semantic Layer™ to create a single source of truth across the board

We also support data mesh architecture, in which Kyvos acts as a customer-facing product layer to consolidate data products from different domains in a single layer, offering a better and clearer view to make better decisions.

Kyvos is a cloud BI acceleration platform designed to work seamlessly with all cloud platforms and is accessible from any BI tool. Our solution enables accelerated analytics at a massive scale without requiring significant changes to the existing analytics ecosystem. By leveraging Kyvos, businesses can harness the full power of their data and unlock new growth opportunities while controlling their cloud computing costs.

To learn more about Kyvos, request a demo now.


What are the top 5 cloud data and analytics trends for 2023?

In the data-driven business scenario, the most crucial cloud and data analytics trends for 2023 will be:

  • A deep focus on instant data access
  • Higher acceptance of the data mesh architecture
  • Data democratization to establish a single source of truth
  • Focus on cloud cost optimization
  • Prioritization of data security mechanisms

What are the benefits of adopting cloud-based data analytics in 2023?

A fully integrated cloud-based data analytics architecture brings the benefits of scalability, reliability, and cost-effective operability to the organization while making it easier to access data anytime from anywhere without compromising its integrity.

What security measures are important for cloud-based data analytics?

Sensitive business data for cloud-based data analytics must be safeguarded with robust protocols like single sign-on, role-based access controls, and multi-level authentication. With these security measures, organizations can secure critical data assets against breaches and other threats.

How does cloud data analytics enable scalability and flexibility?

With powerful on-demand capabilities, cloud data analytics offer limitless flexibility to scale the resources up or down without purchasing or setting up in-house servers or any additional architecture. Users can access files with web-enabled devices to support internal and external collaborations on the go.

What are the emerging technologies driving cloud data analytics?

What are the emerging technologies driving cloud data analytics?
With multi-cloud adoption on the rise, organizations are investing more in cloud-native applications and technologies like Kyvos. As the world’s only analytics acceleration platform, Kyvos enables smart query aggregation, a universal semantic layer for unified data access, and multi-layered security while the platform acts as a product layer in the data mesh architecture.

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