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CockroachDB increases compatibility with existing database tools and skills to enable developers to work efficiently with distributed data processing.
Exasol offers an in-memory database to accelerate analytics on an existing data warehouse, or to unify data from multiple analytic data platforms.
Adoption of graph databases may get a boost from increased standardization, as well as user interfaces targeted at developers and data scientists.
Ventana Research’s 2023 Value Index on analytic data platforms evaluates Redis.
Ventana Research’s 2023 Value Index on analytic data platforms evaluates DataStax.
Ventana Research’s 2023 Value Index on analytic data platforms evaluates Neo4j.
Ventana Research’s 2023 Value Index on analytic data platforms evaluates Cockroach Labs.
Ventana Research’s 2023 Value Index on analytic data platforms evaluates Snowflake.
Ventana Research’s 2023 Value Index on analytic data platforms evaluates EDB.
Promethium provides data fabric and self-service augmented analytics to accelerate time to insight from disparate and distributed data sources.
Ventana Research’s 2023 Value Index on analytic data platforms evaluates PingCAP.
Ventana Research’s 2023 Value Index on analytic data platforms evaluates SingleStore.
Ventana Research’s 2023 Value Index on analytic data platforms evaluates Databricks.
Soda’s data observability software helps data teams and data consumers work collaboratively, building trust in data to boost value, improve decision-making.
Ventana Research’s 2023 Value Index on analytic data platforms evaluates MariaDB.
Ventana Research’s 2023 Value Index on analytic data platforms evaluates Cloudera.
The growing use of data-intensive operational applications reinforces the need for organizations to adopt real-time analytic processing.
Ventana Research’s 2023 Value Index on analytic data platforms evaluates MongoDB.
Data is a fundamental enabler of new business processes and applications, allowing organizations to deliver contextually relevant recommendations, predictions and forecasting to customers and workers, increasing efficiency and improving customer serv
Monitoring telemetry data and computing infrastructure through observability platforms is challenging but key to detecting issues and acting quickly to remedy failures and performance problems.
Ventana Research’s 2023 Value Index on analytic data platforms evaluates Micro Focus.
Ventana Research’s 2023 Value Index on analytic data platforms evaluates Google.
Tamr’s master data management software uses AI/ML to overcome the challenges of maintaining data quality amid the growing volume and variety of data.
Ventana Research’s 2023 Value Index on analytic data platforms evaluates Couchbase.
Ventana Research’s 2023 Value Index on analytic data platforms evaluates Amazon Web Services.
Ventana Research’s 2023 Value Index on analytic data platforms evaluates SAP.
Ventana Research’s 2023 Value Index on analytic data platforms evaluates Actian.
Ventana Research’s 2023 Value Index on analytic data platforms evaluates Teradata.
Ventana Research’s 2023 Value Index on data platforms evaluates Microsoft.
SnapLogic’s Intelligent Integration Platform simplifies and accelerates data integration to make data conveniently available to decision-makers.
Ventana Research’s 2023 Value Index on data platforms evaluates InterSystems.
Ventana Research’s 2023 Value Index on data platforms evaluates Oracle.
The 2023 Analytic Data Platforms Value Index uses a structured methodology to assess how well vendors’ offerings meet buyers’ requirements.
IBM leads the field in Ventana Research’s 2023 Value Indexes on data platforms, receiving high marks across analytic, operational and overall evaluations.
Analyst Matt Aslett shares observations on the evolution of the analytic data platforms market and the implications for analytics applications.
The 2023 Operational Data Platforms Value Index uses a structured methodology to assess how well vendors’ offerings meet buyers’ requirements.
The 2023 Market Agenda for Data will explore smarter methods for using data effectively, providing insights to guide decision-making.
Analyst Matt Aslett shares his observations on the evolution of the operational data platforms market and the implications for operational applications.
The 2023 Data Platforms Value Index uses a structured methodology to assess how well vendors’ offerings meet buyers’ requirements.
Acceldata monitors and manages the reliability of data pipelines and data infrastructure by addressing data infrastructure scaling and performance issues.
Analyst Matt Aslett shares his observations on the evolution of the data platforms market as vendors advance products in response to customer demands.
InterSystems’ cloud data platform supports easy integration, connects data and application silos and provides database management, analytics capabilities.
An organized, well-stocked data pantry reduces time spent on data preparation, incorporates a wide range of data sources and accelerates analysis, insights.
Distributed SQL databases support operational workloads used to run the business, providing scalability and resiliency necessary for business continuity.
This Value Index report evaluates the following vendors which offer products that are considered analytic data platforms as we define it: Actian, Amazon Web Services, Cloudera, Databricks, EDB, Google, IBM, MariaDB, Micro Focus, Microsoft, Oracle, SA
This Value Index market report evaluates the following vendors which offer products that are considered operational data platforms as we define it: Actian, Amazon Web Services, Cloudera, Cockroach Labs, Couchbase, DataStax, EDB, Google, IBM, InterSys
This Value Index report evaluates the following vendors that offer products that address key elements of data platforms to support a combination of both operational and analytic workloads: Actian, Amazon Web Services, Cloudera, EDB, Google, IBM, Inte
To speed data-quality review and get to analysis faster, consider data observability software that uses AI/ML and automation to monitor data.
Oldcastle Infrastructure earned the 2022 Annual Digital Leadership Award in Data for using Fivetran to transform into a data-driven organization.
By accelerating every stage of the analytics life cycle, organizations can achieve the greatest impact in lowering time to insight.
Today’s episode features David Menninger, SVP & Research Director of Technology Research at Ventana Research, talking with Volker Metten and Jeremy Siewert of Tableau about data fabrics, data catalogues, and effective governance for data and analytic
By monitoring and analyzing telemetry data in the form of logs, traces and metrics, organizations can detect issues and act faster to remedy failures and performance problems.
Teradata VantageCloud Lake is an important offering that provides a cloud-native architecture, enabling elastic scalability and support for object storage.
Stibo Systems’ Product Master Data Management application enables consistent product data, improving supply chain visibility for informed decision-making.
Organizations must choose wisely when deciding between in-database analytics or a standalone analytics platform to gain most value, benefit from their data.
Databricks has developed its data lakehouse platform to maximize analytical outcomes from combined data lake and data warehouse functionality.
IBM’s Cloud Pak for Data helps organizations employ a data fabric approach, improving data integration and use of AI and machine learning.
Actian’s Avalanche data platform eliminates data silos, blind spots with a single environment for data integration, management, processing and analytics.
If you’re looking to create a more agile, comprehensive DataOps process, consider data orchestration to meet the needs of modern analytics environments.
Cloudera brings the benefits of large-scale data processing and analytics to its easy-to-use, self-service data platform via a single SaaS offering.
For organizations with large datasets, Ocient’s analytic platform enables complex analytics while offering a high-touch approach to customer engagement.
A semantic layer fills a void left in many analytic architectures. It is a centralized place to define business logic, ensure reporting is consistent, accelerate insights and make data more consumable.
Customer segmentation helps improve the efficiency and effectiveness of the marketing spend, enabling sales to focus on the right leads and companies to improve their margins by targeting high-value opportunities.
Aerospike’s Real-time Data Platform supports intelligent operational applications with high-performance real-time read-write capabilities.
Safeguarding the health of data pipelines is fundamental to ensuring data is integrated and processed in the sequence required to generate business intelligence. The significance of these data pipelines to delivering data-driven business strategies h
Business analytics doesn’t have to be a mystery, yet there are many myths that persist about how to become a data-driven organization. In the age of disruption, organizations need to have access to all of their data, and they must be able to apply a
Information Requirements Across the Organization
Organizations are collecting data from multiple data sources and a variety of systems to enrich their analytics and business intelligence (BI). But collecting data is only half of the equation.
Metadata-based data management functionality has had a role to play within products for data governance and business intelligence for much longer than that, of course, but the emergence of the data catalog as a product category provided a platform fo
Accurate data is critical for efficient business processes and operations, and to inform decision-making, but there are significant challenges to protecting data and ensuring its accuracy.
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 stre
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
Data is an extremely valuable asset for every organization, but it is meaningless until it is used to make actionable decisions. Given the volume of data generated and collected today, using artificial intelligence with machine learning (AI/ML) is th
Data lakes began to emerge 10 years ago in response to the desire for analytic data platforms that could economically store and process large volumes of raw data. These platforms access data from multiple operational applications in a variety of form
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 mu
Big data is valuable. Our benchmark research shows that using big data analytics results in better communication, better alignment of the business, a competitive advantage, better responsiveness and decreased time to market.
In this webinar, David Menninger, SVP and Research Director of Analytics and Data Research at Ventana Research, will share his insights on the analytics market and an understanding on how to successfully evaluate existing and potential new vendors.
The availability of real-time data is changing the way we live and the types of systems we build. Organizations need more immediacy in their operations.
The age of data is here, and all that data has become integral to an organization’s ability to grow and thrive. However, companies struggle with combining data science and technological advancements to establish data intelligence that is unified, sop
For years data governance has been challenging for organizations. There have been too many different data-related technologies to manage and too many manual processes involved. As a result, data governance policies were restrictive and interfered wit
Operating without data is like driving blindfolded. Organizations today need to rely on data more than at any point in the past. This is because understanding the details of your business operations can mean the difference between success and failure
The digital age of data has dramatically transformed organizations by providing the insights that are necessary to confidently make decisions and take action.
Data engineers, who are responsible for monitoring, managing and maintaining data pipelines, are under increasing pressure to deliver high-performance and flexible data integration and processing pipelines that are capable of handling the rising volu
Data is moving to the cloud. As cloud applications have been adopted, this has meant that many critical sources of data for analytics now or soon will live in the cloud. In fact, almost two-thirds (61%) of participants in our research reported that t
The anticipated benefits of cloud computing have encouraged organizations to accelerate adoption of cloud-based applications and services. Data and analytics are no exception, especially as more and more of an organization’s data resides in the cloud
For too long, data governance has been about preventing people from doing things with data. Yes, restrictions and controls over data are absolutely necessary and should be part of every organization’s information architecture.
Artificial intelligence and machine learning (AI/ML) are extremely valuable to organizations. Our research shows that AI/ML help organizations gain a competitive advantage and improve customer experiences, and have a direct impact on the bottom line,
Organizations today increasingly are choosing to store their data and perform their analyses in the cloud. Our research finds that almost one-half (49%) of organizations are already using cloud-based analytics systems, and data is being migrated to t
Data lakes have enormous potential as a source of business intelligence when included as part of an advanced open data architecture.
Analytics are critical to the efficient and effective operation of most modern organizations; to that end, trusted analytics require trusted data. Inaccurate and untrustworthy data means organizations cannot rely on the analyses produced using that d
For decades, organizations have recognized the need to perform analyses that draw upon information from various parts of an organization.
Accurate data is critical for business processes and operations. Billing customers, for example, requires accurate information regarding the product or service, prices, customer names and addresses and personnel authorized to use the product or servi
Big data, the massive amounts of data that today’s organizations collect, store and analyze, can be valuable in many places and many ways.
Data is an extremely valuable asset to almost every organization, and it informs nearly every decision an organization makes.
In today’s dynamic business environment, organizations cannot fly blindly and expect to succeed. There is a trove of internal and externally sourced data available to organizations that can and should be used to improve decision-making.
Apache Spark and massively parallel processing (MPP) analytical databases are designed for different things. The first generation of “big data” architectures relied upon the distributed Hadoop and MapReduce framework for analytical processing. This f
Self-service analytics is a goal for most organizations, but in many cases it has not become a reality. Just two out of five organizations (40%) report that users can analyze data without the assistance of IT. Yet those who are able to operate withou
Operations are continuous in most organizations today and so too is the data these operations generate.
Adoption of cloud and edge computing infrastructure has brought many benefits to organizations of all sizes. It has improved business agility by reducing the need for upfront purchasing, configuration and deployment of infrastructure, and reduced the
Digital transformation is driving organizations to become much more data intensive. Organizations now process information from an increasing number of internal and external sources. There are many more devices generating information, including IoT se
As organizations become more sophisticated in the use of data, the integration of external data grows in importance and frequency.
While the Internet of Things (IoT) may still be unfamiliar to many consumers, businesses are well aware of its potential. More than 90% of participants in our research said that IoT is important to their future operations.
Data lakes can provide organizations significant value and help them improve their business processes.
Organizations face increasing competition and compressed time frames that require intelligent use of all available data.
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
The annual Ventana Research Digital Innovation Awards showcase advances in the productivity and potential of business applications as well as technology that contributes significantly to the improved processes and performance of an organization. Our
Master data management (MDM) is critical to ensuring that your organization has the clean, consistent data needed to operate efficiently and effectively.
Streaming data has been part of the industry landscape for decades but has largely been focused on niche applications in segments with the highest real-time data processing and analytics performance requirements, such as financial services and teleco
In this Analyst Perspective, I will outline the four key traits that I believe are required for a company to be considered data-driven.
We’ve recently published our latest Benchmark Research on Data Governance and it’s fair to say, “you’ve come a long way, baby.” Many of you reading this weren’t around when that phrase was introduced in 1968 to promote Virginia Slims cigarettes, but
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 N
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 o
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
Data governance has always been a critical part of the data and analytics landscape but was for many years seen as a preventative function that was designed to limit access to data to ensure compliance with security and data privacy requirements.
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 a
For many organizations, new technological investment and evolution will be required to facilitate adoption of data mesh. Meanwhile, the concept of the data fabric, a technology-driven approach to managing and governing data across distributed environ
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 exte
The data governance landscape is growing rapidly. Organizations handling vast amounts of data face multiple challenges as more regulations are added to govern sensitive information. Adoption of multi-cloud strategies increases governance concerns wit
The server is a key component of enterprise computing, providing the functional compute resources required to support software applications. Historically, the server was so fundamentally important that it – along with the processor, or processor core
Over a decade ago, I coined the term NewSQL to describe the new breed of horizontally scalable, relational database products. The term was adopted by a variety of vendors that sought to combine the transactional consistency of the relational database
Organizations face a variety of data and analytics challenges resulting from growth and increased scale. Multiple tools and techniques are needed to derive value from various databases. But, adding more systems means adding more complexities, which c
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 applica
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 r
Data governance is an issue that impacts all organizations large and small, new and old, in every industry, and every region of the world. Data governance ensures that an organization’s data can be cataloged, trusted and protected, improving business
Improving the quality of information is cited by organizations as the leading benefit of data preparation activities. Data quality efforts are focused on clean data, but increasingly, the importance of bad data is also recognized. To be more accurate
I recently described the growing level of interest in data mesh which provides an organizational and cultural approach to data ownership, access and governance that facilitates distributed data processing. As I stated in my Analyst Perspective, data
Data mesh is the latest trend to grip the data and analytics sector. The term has been rapidly adopted by numerous vendors — as well as a growing number of organizations —as a means of embracing distributed data processing. Understanding and adopting
Despite widespread and increasing use of the cloud for data and analytics workloads, it has become clear in recent years that, for most organizations, a proportion of data-processing workloads will remain on-premises in centralized data centers or di
Organizations face various challenges with analytics and business intelligence processes, including data curation and modeling across disparate sources and data warehouses, maintaining data quality and ensuring security and governance.
I recently examined how evolving functionality had fueled the adoption of NoSQL databases, recommending that organizations evaluate NoSQL databases when assessing options for data transformation and modernization efforts. This recommendation was base
Today, organizations understand the importance of good external data that can be integrated with internal data to train machine learning models. Our Machine Learning Dynamic Insights research showed that external data adds a significant value in gain
The various NoSQL databases have become a staple of the data platforms landscape since the term entered the IT industry lexicon in 2009 to describe a new generation of non-relational databases. While NoSQL began as a ragtag collection of loosely affi
As businesses become more data-driven, they are increasingly dependent on the quality of their data and the reliability of their data pipelines. Making decisions based on data does not guarantee success, especially if the business cannot ensure that
I recently described the emergence of hydroanalytic data platforms, outlining how the processes involved in generating energy from a lake or reservoir were analogous to those required to generate intelligence from a data lake. I explained how structu
Many organizations invest in data governance out of concern over misuse of data or potential data breaches. These are important considerations and valid aspects of data governance programs. However, good data governance also has positive impacts on o
As I stated when joining Ventana Research, the socioeconomic impacts of the pandemic and its aftereffects have highlighted more than ever the differences between organizations that can turn data into insights and are agile enough to act upon it and t
Organizations analyze the data they collect in a myriad of ways, providing insights and guiding decision-making through mathematics-based metrics. The resulting information can be distributed via traditional reports, visualized in a variety of displa
I recently described how the data platforms landscape will remain divided between analytic and operational workloads for the foreseeable future. Analytic data platforms are designed to store, manage, process and analyze data, enabling organizations t
Today’s world runs on data, so to succeed organizations must use analytics to understand, plan and improve their operations. Ventana Research is conducting benchmark research to understand how organizations apply analytics to data, producing informat
Ventana Research recently announced its 2022 Market Agenda for Data, continuing the guidance we have offered for nearly two decades to help organizations derive optimal value and improve business outcomes.
With the announcement of Ventana Research’s 2022 Market Agenda, our expertise in Digital Business continues to advance the market need for effective investments into technology, and I will outline here the key areas of focus to provide insights to or
Digital transformation efforts are widespread, with most organizations focusing on the innovative use of data. Business users demand real-time, integrated analytics deployed through a unified platform with built-in machine learning (ML) that delivers
The annual Ventana Research Digital Leadership Awards recognize organizations and individuals that utilize technology to advance business and IT. The Digital Leadership Awards showcase the professional leadership and their use of business application
Data platforms are designed to manage and analyze big data, enabling organizations to leverage their data to operate with greater efficiency across on-premises, hybrid and multi-cloud environments. Our Analytics and Data Benchmark Research finds that
Data Catalogs are fundamentally changing the way organizations think about and manage their data.
It has been clear for some time that future enterprise IT architecture will span multiple cloud providers as well as on-premises data centers. As Ventana Research noted in the market perspective on data architectures, the rapid adoption of cloud comp
Breaking into the database market as a new vendor is easier said than done given the dominance of the sector by established database and data management giants, as well as the cloud computing providers. We recently described the emergence of a new br
The need for a COVID-19 vaccination “passport” has prompted some to suggest using blockchain technology as a means of reliably verifying an individual’s status at an international level.
With more and more data available to analyze, organizations are realizing the value that sophisticated analyses using artificial intelligence and machine learning (AI/ML) can provide. The benefits of these analyses are significant: our Dynamic Insigh
Enterprises looking to adopt cloud-based data processing and analytics face a disorienting array of data storage, data processing, data management and analytics offerings.
The availability of real-time data is changing the way we live and the types of systems we build. Organizations need more immediacy in their operations. Nearly half the participants in our Internet of Things research study indicated that it was essen
The age of data is here, and all that data has become integral to an organization’s ability to grow and thrive. However, companies struggle with combining data science and technological advancements to establish data intelligence that is unified, sop
The virtualization of business and the evolution of digital transformation to applications and systems that operate in cloud computing — or the “as-a-service” environment — has fragmented enterprise and data architectures.
When you think about it, events are at the very core of computing, right down to the simplest if-then operation in a spreadsheet. Each event leads to a set of choices, often binary, which then become events in themselves.
Databricks is a data engineering and analytics cloud platform built on top of Apache Spark that processes and transforms huge volumes of data and offers data exploration capabilities through machine learning models.
External data can be valuable to many organizations. It can enrich the internal data that an organization collects and analyzes about its customers, prospects and partners. Planning and operations teams can benchmark an organization’s financial or op
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 dat
For years data governance has been challenging for organizations. There have been too many different data-related technologies to manage and too many manual processes involved. As a result, data governance policies were restrictive and interfered wit
The technology industry throws around a lot of similar terms with different meanings as well as entirely different terms with similar meanings. In this post, I don’t want to debate the meanings and origins of different terms; rather, I’d like to high
Data governance is a hot topic these days. In fact, we are conducting benchmark research on the subject here. With increasing regulations such as the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA), organizati
Collibra is a data governance software company that offers tools for metadata management and data cataloging. The software enables organizations to find data quickly, identify its source and assure its integrity.
The age of data is here, and the value of all that data to organizations continues to increase. Data has, in fact, become integral to an organization’s ability to grow and thrive. So, it is essential that organizations tap into every available source
Rapidminer is a visual enterprise data science platform that includes data extraction, data mining, deep learning, artificial intelligence and machine learning (AI/ML) and predictive analytics. It can support AI/ML processes with data preparation, mo
Master data management (MDM) is critical to ensuring that your organization has the clean, consistent data needed to operate efficiently and effectively. Excellent customer experiences and effective omnichannel engagement often depend on enrichment w
The anticipated benefits of cloud computing have encouraged organizations to accelerate adoption of cloud-based applications and services. Data and analytics are no exception, especially as more and more of an organization’s data resides in the cloud
Confluent Platform is a streaming platform built by the original creators of Apache Kafka. It enables organizations to organize and manage streaming data from various sources. Confluent launched its IPO in June this year and raised $828 million to fu
For too long, data governance has been about preventing people from doing things with data. Yes, restrictions and controls over data are absolutely necessary and should be part of every organization’s information architecture. These controls are nece
We are happy to share some insights about Innovit MDM drawn from our latest Value Index research, which assesses how well vendors’ offerings meet buyers’ requirements.
Human Resources and Finance are critical business functions. Engaging with the analytics associated with these areas will help improve business operations, but in many cases traditional data warehouses and analytics are so disconnected from the busin
Master data management (MDM) is critical to ensuring that your organization has the clean, consistent data needed to operate efficiently and effectively. Excellent customer experiences and effective omnichannel engagement often depend on enrichment w
Teradata introduced some enhancements to its Vantage platform last year in which they expanded its analytics functions and language support, and strengthened tools to improve collaboration between data scientists, business analysts, data engineers an
External data can be valuable to many organizations for a variety of reasons. It can be used by planning and operations teams to benchmark an organization’s financial or operational performance. It can enrich the data an organization collects and ana
Alation recently announced the release of its 2021.1 version, introducing new data governance capabilities, enhancements in search and discovery through data domains, and extended connector and query coverage for data sources.
Master data management (MDM) as a discipline has been around for decades. And MDM software has been evolving over time to help organizations meet their changing data requirements. But if your understanding of MDM software is even a little bit dated,
Everyone talks about data quality, as they should. Our research shows that improving the quality of information is the top benefit of data preparation activities.
Machine learning is valuable for organizations, but it can be hard to deploy. Our Machine Learning Dynamic Insights research identifies that not having enough skilled resources and difficulty building and maintaining ML systems are pressing challenge
The amount of data flowing into organizations is growing exponentially, creating a need to process more data more quickly than ever before.
This report evaluates the following vendors that offer products that deliver analytics and BI as we define it: Amazon.com Inc., Board International, Domo, Infor, Information Builders Inc., IBM, Google LLC, Microsoft Corporation, MicroStrategy, Oracle
This report evaluates the following vendors that offer products that deliver analytics and BI as we define it: Amazon.com Inc., Board International, Domo, Infor, Information Builders Inc., IBM, Google LLC, Microsoft Corporation, MicroStrategy, Oracle
This report evaluates the following vendors that offer products that deliver embedded analytics and business intelligence as we define it: Amazon.com Inc., Board International, Domo, Google LLC, Infor, Information Builders Inc., IBM, Microsoft Corpor
Organizations are becoming more and more data-driven and are looking for ways to accelerate the usage of artificial intelligence and machine learning (AI/ML).
Organizations are accelerating their digital transformation and looking for innovative ways to engage with customers in this new digital era of data management.
Ventana Research recently announced its 2021 Market Agenda for data, continuing the guidance we have offered for nearly two decades to help organizations derive optimal value and improve business outcomes.
Ventana Research has announced its market agenda for 2021, continuing the tradition of transparency in our efforts to educate and guide the technology market but also our independence as we do not share our market agenda or analyst perspectives with
Data is becoming more valuable and more important to organizations. At the same time, organizations have become more disciplined about the data on which they rely to ensure it is robust, accurate and governed properly.
Organizations are dealing with exponentially increasing data that ranges broadly from customer-generated information, financial transactions, edge-generated data and even operational IT server logs.
Businesses are transforming their organizations, building a data culture and deploying sophisticated analytics more broadly than ever.
Traditional on-premises data processing solutions have led to a hugely complex and expensive set of data silos where IT spends more time managing the infrastructure than extracting value from the data.
Organizations are always looking to improve their ability to use data and AI to gain meaningful and actionable insights into their operations, services and customer needs.
For a variety of reasons, organizations are moving their workloads to the cloud. Our research shows that one-third of organizations have their primary data lake platforms in the cloud and most organizations (86%) expect the majority of their data to
For decades, organizations have recognized the need to perform analyses that draw upon information from various parts of an organization. Product profitability analyses require production costs, selling costs and customer service costs.
Ventana Research has awarded Molecula its 2020 Digital Innovation Award for Data. This award acknowledges the technology vendor that best exemplifies innovation in data and associated technologies for supporting information management-related needs.
A data lake is a centralized repository designed to house big data in structured, semi-structured and unstructured form.
Streaming data is transforming how retailers operate. Retail’s evolution from brick-and-mortar to omnichannel has provided organizations with better information about customer behavior while also increasing the expectations of consumers regarding the
Streaming data is transforming how insurance companies provide their services. It can offer critical information needed to underwrite risks with better information, detect and prevent fraudulent claims, deliver world-class customer service and tie to
Streaming data will be transformative to the future of financial services organizations. It can provide the critical, timely information needed to deliver world-class customer service, detect and prevent fraud, tie together disparate legacy systems o
Today’s fast-paced world requires responsiveness in all types of interactions with customers, prospects, partners and employees. Organizations must be able to respond in the moment or risk missing the opportunity altogether. To do this, the systems a
For decades, data integration was a rigid process. Data was processed in batches once a month, once a week or once a day. Organizations needed to make sure those processes were completed successfully—and reliably—so they had the data necessary to mak
Organizations today need to rely on data more than at any point in the past. This is because understanding the details of your business operations can mean the difference between success and failure.
MicroStrategy recently held its annual user conference, which focused on the theme of the “Intelligent Enterprise.”
I was recently asked to identify key modern data architecture trends.
Effectively managing data privacy and security is a high-stakes matter.
Ventana Research recently announced its 2020 research agenda for data, continuing the guidance we’ve offered for nearly two decades to help organizations derive optimal value and improve business outcomes.
In this analyst perspective, Dave Menninger takes a look at data lakes. He explains the term “data lake,” describes common use cases and shares his views on some of the latest market trends.
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