The development, testing and deployment of data pipelines is a fundamental accelerator of data-driven strategies, enabling enterprises to extract data from the operational applications and data platforms designed to run the business and load, integrate and transform it into the analytic data platforms and tools used to analyze the business. As I explained in our recent Data Pipelines Buyers Guide, data pipelines are essential to generating intelligence from data. Healthy data pipelines are...
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Topics:
Analytics,
data operations,
data platforms,
Analytics & Data,
Generative AI,
AI and Machine Learning,
Data Intelligence
As enterprises seek to increase data-driven decision-making, many are investing in strategic data democratization initiatives to provide business users and data analysts with self-service access to data across the enterprise. Such access has long been a goal of many enterprises, but few have achieved it. Only 15% of participants in Ventana Research’s Analytics and Data Benchmark Research say their organization is very comfortable allowing business users to work with data that has not been...
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Topics:
Analytics,
data operations,
Analytics & Data,
AI and Machine Learning,
Data Intelligence,
Data Products,
Data Democratization
We live in an era of uncertainty, not unpredictability. Managing in uncertain times is always difficult, but tools are available to improve the odds for success by making it easier and faster to plan for contingencies and scenarios. Software makes it possible to manage ahead of any future event, connecting the tactical trees to the strategic forest. The purpose of planning is not just to create a plan: Enterprises spend time thinking ahead because it enables leadership teams, executives and...
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Topics:
Office of Finance,
Continuous Planning,
Data Management,
Business Planning,
data operations,
digital finance,
AI and Machine Learning
I have previously written about the functional evolution and emerging use cases for NoSQL databases, a category of non-relational databases that first emerged 15 or so years ago and are now well established as potential alternatives to relational databases. NoSQL is a term used to describe a variety of databases that fall into four primary functional categories: key-value stores, wide-column stores, document-oriented databases and graph databases. Each is worthy of further exploration, which is...
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Topics:
Data,
data operations
In recent years, many enterprises have migrated data platform workloads from on-premises infrastructure to cloud environments, attracted by the promised benefits of greater agility and lower costs. The scale of cloud data platform adoption is illustrated by Ventana Research’s Data Lakes Dynamic Insights research: For two-thirds (66%) of participants, the primary data platform used for analytics is cloud based. As the quantity and importance of the data platform workloads deployed in the cloud...
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Topics:
business intelligence,
Cloud Computing,
data operations,
robotic automation,
Analytics & Data,
Analytic Data Platforms,
AI and Machine Learning
Ventana Research recently announced its 2024 Market Agenda for Analytics and Data, continuing the guidance we have offered for two decades to help enterprises derive optimal value and improve business outcomes.
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Topics:
embedded analytics,
Analytics,
Business Intelligence,
Data Governance,
Data Management,
natural language processing,
data operations,
Process Mining,
Streaming Analytics,
Analytics & Data,
Streaming Data & Events,
operational data platforms,
Analytic Data Platforms
As articulated in Ventana Research’s Data Platforms Buyer’s Guide and DataOps Buyer’s Guide research, the combination of cloud computing and advanced analytics has lowered the cost of storing and processing large volumes of data, accelerating the emergence of new data platform and data operations products that enable organizations to gain operational efficiency and competitive advantage. The right combination of data platform and data management products is essential to ensure that the right...
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Topics:
Data Management,
Data,
Digital Technology,
data operations,
data platforms,
Analytics & Data,
operational data platforms,
Analytic Data Platforms
The phrase ‘big data’ may have largely gone out of fashion, but the concept of storing and processing all relevant data continues to be important for enterprises seeking to be more data-driven. Doing so requires analytic data platforms capable of storing and processing data in multiple formats and data models. This will be an important focus for the forthcoming Data Platforms Buyer’s Guide 2024.
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Topics:
Analytics,
Business Intelligence,
Data Management,
Data,
Digital Technology,
data operations,
Analytics & Data,
AI and Machine Learning
I recently discussed how fashion has a surprisingly significant role to play in the data market as various architectural approaches to data storage and processing take turns enjoying a phase in the limelight. Pendulum swing is a theory of fashion that describes the periodic movement of trends between two extremes, such as short and long hemlines or skinny and baggy/flared trousers. Pendulum swing theory is similarly a factor in data technology trends, with an example being the oscillation...
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Topics:
Analytics,
Cloud Computing,
Data Management,
Data,
Digital Technology,
data operations,
Analytics & Data,
AI and Machine Learning
I have previously written about the functional evolution and emerging use cases for NoSQL databases, a category of non-relational databases that first emerged 15 or so years ago and are now well established as potential alternatives to relational databases. NoSQL is a term used to describe a variety of databases that fall into four primary functional categories: key-value stores, wide-column stores, document-oriented databases and graph databases. Each is worthy of further exploration, which is...
Read More
Topics:
Cloud Computing,
Data,
Digital Technology,
data operations,
Analytics & Data,
operational data platforms