ISG Software Research Analyst Perspectives

Sisense is Sensible for Embedded Analytics and BI

Posted by David Menninger on 07 December 2022

Embedded business intelligence (BI) continues to transform the business landscape, enabling organizations to quickly interpret data and convert it into actionable insights. It allows organizations to extract information in real time and answer wide-ranging business questions. Embedding analytics helps tackle the issue of extracting information from data which is a time-consuming process. Our... Read More

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

IBM Builds on Analytics and BI Foundation

Posted by David Menninger on 29 November 2022

In today’s data-driven world, organizations need real-time access to up-to-date, high-quality data and analysis to keep pace with changing market dynamics and make better strategic decisions. By mining meaningful insights from enterprise data quickly, they gain a competitive advantage in the market. Yet, organizations face a multitude of challenges when transitioning into an analytics-driven... Read More

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

Mind the Gap Between Data and Analytics

Posted by David Menninger on 16 November 2022

If you’ve ever been to London, you are probably familiar with the announcements on the London Underground to “mind the gap” between the trains and the platform. I suggest we also need to mind the gap between data and analytics. These worlds are often disconnected in organizations and, as a result, it limits their effectiveness and agility. Part of the issue is that data and analytics tasks are... Read More

Topics: embedded analytics, Analytics, Business Intelligence, Data Governance, Data Management, data operations, Analytics and Data

MLOps: A Disciplined Approach That Increases Organizational Agility

Posted by David Menninger on 20 October 2022

Artificial intelligence and machine learning are valuable to data and analytics activities. Our research shows that organizations using AI/ML report gaining competitive advantage, improving customer experiences, responding faster to opportunities and threats and improving the bottom line with increased sales and lower costs. No wonder nearly 9 in 10 (87%) research participants report using AI/ML... Read More

Topics: Analytics, AI and Machine Learning

Celonis Improves Business Processes with Process Mining

Posted by David Menninger on 14 October 2022

As I recently pointed out, process mining has emerged as a pivotal technology for data-driven organizations to discover, monitor and improve processes through use of real-time event data, transactional data and log files. With recent advancements, process mining has become more efficient at discovering insights in complex processes using algorithms and visualizations. Organizations use it to... Read More

Topics: Analytics, Business Intelligence, Process Mining, Streaming Analytics, AI and Machine Learning

Process Mining improves Business Processes

Posted by David Menninger on 04 October 2022

Process mining is defined as the analysis of application telemetry including log files, transaction data and other instrumentation to understand and improve operational processes. Log data provides an abundance of information about what operations are occurring, the sequences involved in the processes, how long the processes are taking and whether or not the processes are completed successfully.... Read More

Topics: Analytics, Business Intelligence, Process Mining, AI and Machine Learning

Augmented Intelligence Reduces Dependency on AI/ML Skill Sets

Posted by David Menninger on 15 September 2022

Business intelligence has evolved. It now includes a spectrum of analytics, one of the most promising of which has been described as augmented intelligence. Some organizations have used the term to describe the practical reality that artificial intelligence with machine learning is not replacing human intelligence, but augmenting it. The term also represents the application of AI/ML to make... Read More

Topics: Analytics, Business Intelligence, natural language processing, Collaborative & Conversational Computing, Analytics and Data, AI and Machine Learning

Embed Analytics for Greater Reach and More Responsiveness

Posted by David Menninger on 18 August 2022

When I looked at the state of analytics recently, it was clear that analytics are not as widely deployed within organizations as they should be. Only 23% of participants in our Analytics and Data Benchmark Research reported that more than one-half of their organization’s workforce are using analytics. There are many elements to becoming a data-driven organization, as my colleague Matt Aslett... Read More

Topics: embedded analytics, Analytics, Analytics and Data

Qlik Advances Self-Service Analytics and Business Intelligence

Posted by David Menninger on 11 August 2022

The analytics and business intelligence market landscape continues to grow as more organizations seek robust tools and capabilities to visualize and better understand data. BI systems are used to perform data analysis, identify market trends and opportunities and streamline business processes. They can collect and combine data from internal and external systems to present a holistic view. BI... Read More

Topics: Analytics, Business Intelligence, Data Governance, Data Management, Analytics and Data, AI and Machine Learning

Tableau Brings Business Intelligence to Business Users

Posted by David Menninger on 26 July 2022

Organizations are collecting vast amounts of data every day, utilizing business intelligence software and data visualization to gain insights and identify patterns and errors in the data. Making sense of these patterns can enable an organization to gain an edge in the marketplace and plan more strategically. Tableau is a data visualization software company, acquired by Salesforce in 2019, that... Read More

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

Data-Driven Agenda for Organizations

Posted by Matt Aslett on 21 July 2022

When joining Ventana Research, I noted that the need to be more data-driven has become a mantra among large and small organizations alike. Data-driven organizations stand to gain competitive advantage, responding faster to worker and customer demands for more innovative, data-rich applications and personalized experiences. Being data-driven is clearly something to aspire to. However, it is also a... Read More

Topics: embedded analytics, Analytics, Business Intelligence, Data Governance, Data Integration, Data, Digital Technology, natural language processing, data lakes, data operations, Streaming Analytics, Streaming Data Events, Analytics and Data, AI and Machine Learning

TigerGraph Promotes Graph Database for Data Science with ML Workbench

Posted by Matt Aslett on 14 July 2022

I recently wrote about the growing range of use cases for which NoSQL databases can be considered, given increased breadth and depth of functionality available from providers of the various non-relational data platforms. As I noted, one category of NoSQL databases — graph databases — are inherently suitable for use cases that rely on relationships, such as social media, fraud detection and... Read More

Topics: business intelligence, Analytics, Cloud Computing, Data, Digital Technology, Analytics and Data, AI and Machine Learning

Ahana Offers Managed-Services Approach to Simplify Presto Adoption

Posted by Matt Aslett on 29 June 2022

I previously described the concept of hydroanalytic data platforms, which combine the structured data processing and analytics acceleration capabilities associated with data warehousing with the low-cost and multi-structured data storage advantages of the data lake. One of the key enablers of this approach is interactive SQL query engine functionality, which facilitates the use of existing... Read More

Topics: Analytics, Business Intelligence, Cloud Computing, Data, Digital Technology, data lakes, data operations, Analytics and Data, AI and Machine Learning

Dremio Embraces Data Lakehouse with Cloud Launch

Posted by Matt Aslett on 24 June 2022

I previously explained how the data lakehouse is one of two primary approaches being adopted to deliver what I have called a hydroanalytic data platform. Hydroanalytics involves the combination of data warehouse and data lake functionality to enable and accelerate analysis of data in cloud storage services. The term data lakehouse has been rapidly adopted by several vendors in recent years to... Read More

Topics: business intelligence, Analytics, Data, data lakes

MariaDB Offers One Database for All Workloads

Posted by Matt Aslett on 14 June 2022

As I recently described, it is anticipated that the majority of database workloads will continue to be served by specialist data platforms targeting operational and analytic workloads, albeit with growing demand for hybrid data processing use-cases and functionality. Specialist operational and analytic data platforms have historically been the since preferred option, but there have always been... Read More

Topics: Analytics, Business Intelligence, Cloud Computing, Data, Digital Technology, Analytics and Data

Disentangling and Demystifying Data Mesh and Data Fabric

Posted by Matt Aslett on 02 June 2022

I recently wrote about the potential benefits of data mesh. As I noted, data mesh is not a product that can be acquired, or even a technical architecture that can be built. It’s an organizational and cultural approach to data ownership, access and governance. While the concept of data mesh is agnostic to the technology used to implement it, technology is clearly an enabler for data mesh. For many... Read More

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

SingleStore Positions Hybrid Data Processing for Data Intensity

Posted by Matt Aslett on 25 May 2022

I recently described the use cases driving interest in hybrid data processing capabilities that enable analysis of data in an operational data platform without impacting operational application performance or requiring data to be extracted to an external analytic data platform. Hybrid data processing functionality is becoming increasingly attractive to aid the development of intelligent... Read More

Topics: Analytics, Business Intelligence, Cloud Computing, Data, Digital Technology, Analytics and Data, AI and Machine Learning

Oracle Positions to Address Any and All Data Platform Needs

Posted by Matt Aslett on 05 May 2022

I recently described how the operational data platforms sector is in a state of flux. There are multiple trends at play, including the increasing need for hybrid and multicloud data platforms, the evolution of NoSQL database functionality and applicable use-cases, and the drivers for hybrid data processing. The past decade has seen significant change in the emergence of new vendors, data models... Read More

Topics: business intelligence, Analytics, Data Integration, Data, AI and Machine Learning

Denodo Advancing Data Virtualization in the Cloud

Posted by David Menninger on 28 April 2022

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... Read More

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

Real-Time Data Processing Requires More Agile Data Pipelines

Posted by Matt Aslett on 26 April 2022

I recently wrote about the importance of data pipelines and the role they play in transporting data between the stages of data processing and analytics. Healthy data pipelines are necessary to ensure data is integrated and processed in the sequence required to generate business intelligence. The concept of the data pipeline is nothing new of course, but it is becoming increasingly important as... Read More

Topics: Analytics, Business Intelligence, Data Governance, Data Integration, Data, Digital Technology, Digital transformation, data lakes, data operations, Streaming Data Events, Analytics and Data, AI and Machine Learning