ISG Software Research Analyst Perspectives

InterSystems Transforming Organizations with Cloud Smart Data Fabric

Posted by Matt Aslett on 27 December 2022

The shift from on-premises server infrastructure to cloud-based and software-as-a-service (SaaS) models has had a profound impact on the data and analytics architecture of many organizations in recent years. More than one-half of participants (59%) in Ventana Research’s Analytics and Data Benchmark research are deploying data and analytics workloads in the cloud, and a further 30% plan to do so.... Read More

Topics: Business Intelligence, Cloud Computing, Data Management, Data, natural language processing, data operations, analytic data platforms, Analytics and Data, AI and Machine Learning

Exploring the Case for Distributed SQL Databases

Posted by Matt Aslett on 22 December 2022

There is always space for innovation in the data platforms sector, and new vendors continue to emerge at regular intervals with new approaches designed to serve specialist data storage and processing requirements. Factors including performance, reliability, security and scalability provide a focal point for new vendors to differentiate from established vendors, especially for the most demanding... Read More

Topics: Cloud Computing, Data

Monte Carlo Bets on the Future of Data Observability

Posted by Matt Aslett on 13 December 2022

Earlier this year, I wrote about the increasing importance of data observability, an emerging product category that takes advantage of machine learning (ML) and Data Operations (DataOps) to automate the monitoring of data used for analytics projects to ensure its quality and lineage. Monitoring the quality and lineage of data is nothing new. Manual tools exist to ensure that it is complete, valid... Read More

Topics: Business Intelligence, Cloud Computing, Data Management, Data, data operations

SQream if You Want to Analyze Data Faster

Posted by Matt Aslett on 08 December 2022

One of the most significant considerations when choosing an analytic data platform is performance. As organizations compete to benefit most from being data-driven, the lower the time to insight the better. As data practitioners have learnt over time, however, lowering time to insight is about more than just high-performance queries. There are opportunities to improve time to insight throughout... Read More

Topics: Business Intelligence, Data, data operations, analytic data platforms, AI and Machine Learning

Teradata Goes Cloud Native with VantageCloud Lake

Posted by Matt Aslett on 01 December 2022

Organizations are increasingly utilizing cloud object storage as the foundation for analytic initiatives. There are multiple advantages to this approach, not least of which is enabling organizations to keep higher volumes of data relatively inexpensively, increasing the amount of data queried in analytics initiatives. I assert that by 2024, 6 in ten organizations will use cloud-based technology... Read More

Topics: Teradata, Data Governance, Data Management, Data, data operations, analytic data platforms, Vantage platform

The Arguments For, and Against, In-Database Machine Learning

Posted by Matt Aslett on 23 November 2022

Almost all organizations are investing in data science, or planning to, as they seek to encourage experimentation and exploration to identify new business challenges and opportunities as part of the drive toward creating a more data-driven culture. My colleague, David Menninger, has written about how organizations using artificial intelligence and machine learning (AI/ML) report gaining... Read More

Topics: Data Governance, Data Management, Data, data operations, analytic data platforms, Analytics and Data, AI and Machine Learning

Databricks Lakehouse Platform Maximizes Analytical Value

Posted by Matt Aslett on 16 November 2022

I have previously written about growing interest in the data lakehouse as one of the design patterns for delivering hydroanalytics analysis of data in a data lake. Many organizations have invested in data lakes as a relatively inexpensive way of storing large volumes of data from multiple enterprise applications and workloads, especially semi- and unstructured data that is unsuitable for storing... Read More

Topics: Business Intelligence, Data Governance, Data Management, Data, Streaming Data Events, analytic data platforms, AI and Machine Learning

IBM’s Cloud Pak for Data Builds a Foundation for Data Fabric

Posted by Matt Aslett on 08 November 2022

I have written recently about the similarities and differences between data mesh and data fabric. The two are potentially complementary. Data mesh is an organizational and cultural approach to data ownership, access and governance. Data fabric is a technical approach to automating data management and data governance in a distributed architecture. There are various definitions of data fabric, but... Read More

Topics: Business Intelligence, Cloud Computing, Data Governance, Data Management, Data, data operations, AI and Machine Learning

Actian Manages Avalanches of Data

Posted by Matt Aslett on 01 November 2022

In their pursuit to be data-driven, organizations are collecting and managing more data than ever before as they attempt to gain competitive advantage and respond faster to worker and customer demands for more innovative, data-rich applications and personalized experiences. As data is increasingly spread across multiple data centers, clouds and regions, organizations need to manage data on... Read More

Topics: Data Management, Data, data operations, analytic data platforms

Orchestrating Data Pipelines Facilitates Data-Driven Analytics

Posted by Matt Aslett on 25 October 2022

I have written a few times in recent months about vendors offering functionality that addresses data orchestration. This is a concept that has been growing in popularity in the past five years amid the rise of Data Operations (DataOps), which describes more agile approaches to data integration and data management. In a nutshell, data orchestration is the process of combining data from multiple... Read More

Topics: Data Management, Data, data operations, Analytics and Data, AI and Machine Learning

Cloudera Embraces SaaS with Data Lakehouse Launch

Posted by Matt Aslett on 18 October 2022

Ventana Research’s Data Lakes Dynamics Insights research illustrates that while data lakes are fulfilling their promise of enabling organizations to economically store and process large volumes of raw data, data lake environments continue to evolve. Data lakes were initially based primarily on Apache Hadoop deployed on-premises but are now increasingly based on cloud object storage. Adopters are... Read More

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

Ocient Delivers Ad Hoc Analytics on Hyperscale Workloads

Posted by Matt Aslett on 12 October 2022

I have written before about the continued use of specialist operational and analytic data platforms. Most database products can be used for operational or analytic workloads, and the number of use cases for hybrid data processing is growing. However, a general-purpose database is unlikely to meet the most demanding operational or analytic data platform requirements. Factors including performance,... Read More

Topics: business intelligence, Cloud Computing, Data Management, Data, analytic data platforms, Analytics and Data

Aerospike Has a Data Platform for Real-Time Intelligent Applications

Posted by Matt Aslett on 06 October 2022

Earlier this year I described the growing use-cases for hybrid data processing. Although it is anticipated that the majority of database workloads will continue to be served by specialist data platforms targeting operational and analytic workloads respectively, there is increased demand for intelligent operational applications infused with the results of analytic processes, such as... Read More

Topics: Business Intelligence, Cloud Computing, Data, Streaming Data Events, analytic data platforms, AI and Machine Learning

Astronomer’s Cloud-Based Data Orchestration Brings Efficiency

Posted by Matt Aslett on 29 September 2022

I have recently written about the organizational and cultural aspects of being data-driven, and the potential advantages data-driven organizations stand to gain by responding faster to worker and customer demands for more innovative, data-rich applications and personalized experiences. I have also explained that data-driven processes require more agile, continuous data processing, with an... Read More

Topics: Cloud Computing, Data Management, Data, data operations, Analytics and Data

The Data Catalog is Indispensable for Good Data Governance

Posted by Matt Aslett on 21 September 2022

The data catalog has become an integral component of organizational data strategies over the past decade, serving as a conduit for good data governance and facilitating self-service analytics initiatives. The data catalog has become so important, in fact, that it is easy to forget that just 10 years ago it did not exist in terms of a standalone product category. Metadata-based data management... Read More

Topics: business intelligence, Data Governance, Data Management, Data, data operations, Analytics and Data

Confluent Addresses Data Governance for Data in Motion

Posted by Matt Aslett on 09 September 2022

I recently wrote about the need for organizations to take a holistic approach to the management and governance of data in motion alongside data at rest. As adoption of streaming data and event processing increases, it is no longer sufficient for streaming data projects to exist in isolation. Data needs to be managed and governed regardless of whether it is processed in batch or as a stream of... Read More

Topics: Big Data, Cloud Computing, Data Governance, Streaming Analytics, Streaming Data Events

Rockset Offers Cloud-Based Real-Time Analytics

Posted by Matt Aslett on 30 August 2022

I have written recently about increased demand for data-intensive applications infused with the results of analytic processes, such as personalization and artificial intelligence (AI)-driven recommendations. Almost one-quarter of respondents (22%) to Ventana Research’s Analytics and Data Benchmark Research are currently analyzing data in real time, with an additional 10% analyzing data every... Read More

Topics: Cloud Computing, Data, Streaming Analytics, Streaming Data Events, analytic data platforms, Analytics and Data

Streaming Data Success Relies on Managing Data in Motion and At Rest

Posted by Matt Aslett on 16 August 2022

I recently noted that as demand for real-time interactive applications becomes more pervasive, the use of streaming data is becoming more mainstream. Streaming data and event processing has been part of the data landscape for many decades, but for much of that time, data streaming was a niche activity. Although adopted in industry segments with high-performance, real-time data processing and... Read More

Topics: Big Data, Data, Streaming Analytics, Streaming Data Events, Analytics and Data

Ascend.io Automates Data Engineering

Posted by Matt Aslett on 09 August 2022

I have recently written about the importance of healthy data pipelines to ensure data is integrated and processed in the sequence required to generate business intelligence, and the need for data pipelines to be agile in the context of real-time data processing requirements. Data engineers, who are responsible for monitoring, managing and maintaining data pipelines, are under increasing pressure... Read More

Topics: Big Data, Cloud Computing, Data Management, Data, data operations

Neo4j Expands Data Science Focus with New Managed Service

Posted by Matt Aslett on 03 August 2022

I recently explained how emerging application requirements were expanding the range of use cases for NoSQL databases, increasing adoption based on the availability of enhanced functionality. These intelligent applications require a close relationship between operational data platforms and the output of data science and machine learning projects. This ensures that machine learning and predictive... Read More

Topics: Business Intelligence, Data, analytic data platforms, AI and Machine Learning