Ventana Research recently announced its 2023 Market Agenda for Data, continuing the guidance we have offered for two decades to help organizations derive optimal value and improve business outcomes.
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Topics:
Cloud Computing,
Data Governance,
Data Management,
Data,
Digital Technology,
data operations,
Analytics & Data,
Streaming Data & Events,
operational data platforms,
Analytic Data Platforms
Ventana Research uses the term “data pantry” to describe a method of data storage (and the technology and process blueprint for its construction) created for a specific set of users and use cases in business-focused software. It’s a pantry because all the data one needs is readily available and easily accessible, with labels that are immediately recognized and understood by the users of the application. In tech speak, this means the semantic layer is optimized for the intended audience. It is...
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Topics:
Continuous Planning,
Business Intelligence,
Data Management,
Business Planning,
Data,
Financial Performance Management,
Enterprise Resource Planning,
continuous supply chain,
data operations,
digital finance,
AI & Machine Learning,
profitability management,
Analytics & Data,
Streaming Data & Events
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 and processing in a data warehouse. However, early data lake projects lacked structured data...
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Topics:
Business Intelligence,
Data Governance,
Data Management,
Data,
AI & Machine Learning,
Streaming Data & Events,
Analytic Data Platforms
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 also shifting from data lakes based on homegrown scripts and code to open standards and open...
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Topics:
Business Intelligence,
Data Governance,
Data Management,
Data,
data operations,
AI & Machine Learning,
Analytics & Data,
Streaming Data & Events,
operational data platforms,
Analytic Data Platforms
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 personalization and artificial intelligence-driven recommendations. There are multiple data platform approaches to...
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Topics:
Business Intelligence,
Cloud Computing,
Data,
AI & Machine Learning,
Streaming Data & Events,
operational data platforms,
Analytic Data Platforms
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 events. This requirement has resulted in established data management vendors increasing their focus on...
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Topics:
Big Data,
Cloud Computing,
Data Governance,
Streaming Analytics,
Streaming Data & Events
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 hour. There are multiple data platform approaches to delivering real-time data processing and analytics...
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Topics:
Cloud Computing,
Data,
Streaming Analytics,
Analytics & Data,
Streaming Data & Events,
operational data platforms,
Analytic Data Platforms
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 analytics requirements such as financial services and telecommunications, data streaming was far less...
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Topics:
Big Data,
Data,
Streaming Analytics,
Analytics & Data,
Streaming Data & Events
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 telecommunications. As demand for real-time interactive applications becomes more pervasive, streaming data is becoming a more mainstream pursuit, aided by the proliferation of open-source streaming data and event technologies, which have lowered the cost...
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Topics:
Data,
Streaming Analytics,
Streaming Data & Events,
operational data platforms
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 somewhat vague concept without clear definition. We know data-driven organizations when we see them...
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Topics:
embedded analytics,
Analytics,
Business Intelligence,
Data Governance,
Data Integration,
Data,
Digital Technology,
natural language processing,
data lakes,
data operations,
Digital Business,
Streaming Analytics,
AI & Machine Learning,
data platforms,
Analytics & Data,
Streaming Data & Events