David Menninger's Analyst Perspectives

Palantir Operationalizes Analytics and Data for Actions and Decisions

Posted by David Menninger on Aug 26, 2022 3:00:00 AM

Organizations are managing and analyzing large datasets every day, identifying patterns and generating insights to inform decisions. This can provide numerous benefits for an organization, such as improved operational efficiency, cost optimization, fraud detection, competitive advantage and enhanced business processes. By bringing the right, actionable data to the right user, organizations can potentially speed up processes and make more effective operational decisions.

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Topics: embedded analytics, Analytics, Business Intelligence, Internet of Things, Streaming Analytics, AI & Machine Learning

Expanding the Analytics Continuum: From Analysis to Action

Posted by David Menninger on Aug 2, 2022 3:00:00 AM

I often use the term “analytics” to refer to a broad set of capabilities, deliberately broader than business intelligence. In this Perspective, I’d like to share what decision-makers should consider as they evaluate the range of analytics requirements for their organization.

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Topics: Business Intelligence, natural language processing, AI and Machine Learning, Streaming Analytics, Analytics & Data

Zoho Unifies Data and Analytics

Posted by David Menninger on Jul 7, 2022 3:00:00 AM

Organizations are continuously increasing the use of analytics and business intelligence to turn data into meaningful and actionable insights. Our Analytics and Data Benchmark Research shows some of the benefits of using analytics: Improved efficiency in business processes, improved communication and gaining a competitive edge in the market top the list. With a unified BI system, organizations can have a comprehensive view of all organizational data to better manage processes and identify opportunities.

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Topics: business intelligence, embedded analytics, Data Governance, Data Management, natural language processing, AI and Machine Learning, data operations, Streaming Analytics, Streaming Data & Events, operational data plaftforms

Denodo Advancing Data Virtualization in the Cloud

Posted by David Menninger on Apr 28, 2022 3:00:00 AM

Organizations have been using data virtualization to collect and integrate data from various sources, and in different formats, to create a single source of truth without redundancy or overlap, thus improving and accelerating decision-making giving them a competitive advantage in the market. Our research shows that data virtualization is popular in the big data world. One-quarter (27%) of participants in our Data Lake Dynamic Insights Research reported they were currently using data virtualization, and another two-quarters (46%) planned to include data virtualization in the future. Even more interesting, those who are using data virtualization reported higher rates of satisfaction (79%) with their data lake than those who are not (36%). Our Analytics and Data Benchmark Research shows more than one-third of organizations (37%) are using data virtualization in that context. Here, too, those using data virtualization reported higher levels of satisfaction (88%) than those that are not (66%).

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Topics: embedded analytics, Analytics, Business Intelligence, AI and Machine Learning, Streaming Analytics

Don’t Rely on Dashboards for Real-Time Analytics

Posted by David Menninger on Mar 31, 2022 3:00:00 AM

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.

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Topics: Analytics, Business Intelligence, Internet of Things, Data, Digital Technology, AI and Machine Learning, Streaming Analytics, Analytics & Data, Streaming Data & Events

AtScale Universal Semantic Layer Democratizes and Scales Analytics

Posted by David Menninger on Feb 10, 2022 3:00:00 AM

Organizations of all sizes are dealing with exponentially increasing data volume and data sources, which creates challenges such as siloed information, increased technical complexities across various systems and slow reporting of important business metrics. Migrating to the cloud does not solve the problems associated with performing analytics and business intelligence on data stored in disparate systems. Also, the computing power needed to process large volumes of data consists of clusters of servers with hundreds or thousands of nodes that can be difficult to administer. Our Analytics and Data Benchmark Research shows that organizations have concerns about current analytics and BI technology. Findings include difficulty integrating data with other business processes, systems that are not flexible enough to scale operations and trouble accessing data from various data sources.

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Topics: Analytics, Business Intelligence, Data Integration, Data, data lakes, AI and Machine Learning, data operations, Streaming Analytics

What Makes a Metric a KPI?

Posted by David Menninger on Nov 9, 2021 3:00:00 AM

How does your organization define and display its metrics? I believe many organizations are not defining and displaying metrics in a way that benefits them most. If an organization goes through the trouble of measuring and reporting on a metric, the analysis ought to include all the information needed to evaluate that metric effectively. A number, by itself, does not provide any indication of whether the result is good or bad. Too often, the reader is expected to understand the difference, but why leave this evaluation to chance? Why not be more explicit about what results are expected?

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Topics: business intelligence, Analytics, Internet of Things, Data, Digital Technology, Streaming Analytics, AI & Machine Learning

Using Event Data in Financial Services to Improve Business Processes

Posted by David Menninger on Nov 3, 2021 3:00:00 AM

Our research shows that nearly all financial service organizations (97%) consider it important to accelerate the flow of information and improve responsiveness. Even just a few years ago, capturing and evaluating this information quickly was much more challenging, but with the advent of streaming data technologies that capture and process large volumes of data in real time, financial service organizations can quickly turn events into valuable business outcomes in the form of new products and services or revenue.

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Topics: Analytics, Internet of Things, Data, Digital Technology, Streaming Analytics

Use External Data Platform to Improve Analytics

Posted by David Menninger on Oct 19, 2021 3:00:00 AM

Access to external data can provide a competitive advantage. Our research shows that more than three-quarters (77%) of participants consider external data to be an important part of their machine learning (ML) efforts. The most important external data source identified is social media, followed by demographic data from data brokers. Organizations also identified government data, market data, environmental data and location data as important external data sources. External data is not just part of ML analyses though. Our research shows that external data sources are also a routine part of data preparation processes, with 80% of organizations incorporating one or more external data sources. And a similar proportion of participants in our research (84%) include external data in their data lakes.

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Topics: Analytics, Business Intelligence, Internet of Things, Data, Digital Technology, AI and Machine Learning, Streaming Data, Streaming Analytics

The 2021 Market Agenda for Analytics: Converting Data Into Insights

Posted by David Menninger on Feb 24, 2021 3:00:00 AM

Ventana Research recently announced its 2021 market agenda for Analytics, continuing the guidance we’ve offered for nearly two decades to help organizations derive optimal value from technology investments to improve business outcomes.

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Topics: embedded analytics, Analytics, Business Intelligence, natural language processing, AI and Machine Learning, Process Mining, Streaming Analytics