Ventana Research recently announced its 2023 Market Agenda for Analytics, continuing the guidance we have offered for nearly two decades to help organizations derive optimal value from technology investments to improve business outcomes.
The 2023 Market Agenda for Analytics: Empowering Workforces to Engage
Topics: embedded analytics, Analytics, Business Intelligence, Data, Digital Technology, natural language processing, Process Mining, Analytics & Data, Collaborative & Conversational Computing
2023 Digital Technology Market Agenda: Innovation for Digital Agility
I’m proud to share Ventana Research’s 2023 Market Agenda for Digital Technology. Our focus in this agenda is to deliver expertise to help organizations prioritize technology investments that improve customer, partner and workforce experiences while also increasing organizational effectiveness and agility.
Topics: Analytics, Cloud Computing, Internet of Things, Data, Digital Technology, blockchain, AI and Machine Learning, mobile computing, extended reality, robotic automation, Collaborative & Conversational Computing
Make Intelligent Decisions with Decision Intelligence
For far too long, business intelligence technologies have left the rest of the exercise to the reader. Many of these tools do an excellent job providing information in an interactive way that lets organizations dive into the data and learn a lot about what has happened across all aspects of the business. More recently, many of these tools have added augmented intelligence capabilities that help explain why things happened. But rarely did any of these tools provide information about what to do or how to evaluate the alternative ways in which you might respond.
Topics: business intelligence, Analytics, Digital Technology, AI and Machine Learning, Analytics & Data
Analytics processes are all about how organizations use data to create metrics that help manage and improve operations. Yet, the discipline applied to analytics processes seems to be lacking compared to data processes. I’ve pointed out that the weak link in data governance is often analytics. Organizations can also do a better job tying AnalyticOps to DataOps and do more to define and manage metrics. Our research has shown that creating and managing metrics in a semantic model improves analytics processes.
Topics: Analytics, Business Intelligence, Data Governance, Data, Digital Technology, Analytics & Data
Cloud Computing Realities Part 4 — Security and Governance
In previous perspectives in this series, I’ve discussed some of the realities of cloud computing including costs, hybrid and multi-cloud configurations and business continuity. This perspective examines the realities of security and regulatory concerns associated with cloud computing. These issues are often cited by our research participants as reasons they are not embracing the cloud. To be fair, the majority of our research participants are embracing the cloud. However, among those that have not yet made the transition to the cloud, security and regulatory concerns are among the most common issues cited across the various studies we have conducted.
Topics: Analytics, Business Intelligence, Cloud Computing, Data Governance, Digital Technology, AI & Machine Learning, Analytics & Data, Governance & Risk
Recognize and Plan for the AI and Machine Learning Skills Gap
Recently, I suggested you need to “mind the gap” between data and analytics. This perspective addresses another gap — the gap in skills between business intelligence (BI) and artificial intelligence/machine learning (AI/ML).
Topics: Analytics, Business Intelligence, Digital Technology, AI & Machine Learning, Analytics & Data
Cloud Computing Realities Part 3: Business Continuity
In my previous perspectives on cloud computing, I addressed some of the realities of cloud costs as well as hybrid and multi-cloud architectures. In the midst of the pandemic, my colleague, Mark Smith, authored a series of perspectives on considerations for business continuity in general, beginning with this look at some of the investments organizations must make to mitigate the risk of business disruptions. In this perspective, I’d like to address some of the realities of business continuity and cloud computing and how they impact the digital technologies of an organization. The cloud can be both advantageous and disadvantageous when it comes to providing business continuity.
Topics: Business Continuity, Cloud Computing, Digital Technology, digital business
Cloud Computing Realities Part 2: Hybrid and Multi-Cloud Architectures
In my first perspective on cloud computing realities, I covered some of the cost considerations associated with cloud computing and how the cloud costing model may be different enough from on-premises models that some organizations are taken by surprise. In this perspective. I’d like to focus on realities of hybrid and multi-cloud deployments.
Topics: Cloud Computing, Digital Technology
The migration to cloud is obvious. Organizations are adopting cloud computing for all variety of applications and use cases. Managed cloud services, commonly referred to as software as a service (SaaS), offer many benefits to organizations including significantly reduced labor costs for system administration and maintenance, as many of these costs are shifted to the software vendor. SaaS also provides organizations with faster time to value as they adopt new technologies by eliminating the need to acquire and configure hardware, and it also eliminates the need to install software. In fact, we assert that by 2025, nine in 10 organizations will be using multiple cloud applications in order to minimize the costs of administration and maintenance. Yet, there are some challenges associated with cloud computing I’d like to address in a series of Analyst Perspectives:
Topics: Cloud Computing, Digital Technology
Don’t Rely on Dashboards for Real-Time Analytics
I have written previously that the world of data and analytics will become more and more centered around real-time, streaming data. Data is created constantly and increasingly is being collected simultaneously. Technology advances now enable organizations to process and analyze information as it is being collected to respond in real time to opportunities and threats. Not all use cases require real-time analysis and response, but many do, including multiple use cases that can improve customer experiences. For example, best-in-class e-commerce interactions should provide real-time updates on inventory status to avoid stock-out or back-order situations. Customer service interactions should provide real-time recommendations that minimize the time to resolution. Location-based offers should be targeted at the customer’s current location, not their location several minutes ago. Another domain where real-time analyses are critical is internet of things (IoT) applications. Additionally, use cases like predictive maintenance require timely information to prevent equipment failures that help avoid additional costs and damage.
Topics: Analytics, Business Intelligence, Internet of Things, Data, Digital Technology, AI and Machine Learning, Streaming Analytics, Analytics & Data, Streaming Data & Events