I recently wrote about the development, testing and deployment of data pipelines as a fundamental accelerator of data-driven strategies. As I explained in the 2023 Data Orchestration Buyers Guide, today’s analytics environments require agile data pipelines that can traverse multiple data-processing locations and evolve with business needs.
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Topics:
Analytics,
data operations,
AI & Machine Learning,
data platforms,
Analytics & Data,
Generative AI,
Data Intelligence
I wrote recently about the role that data intelligence has in enabling enterprises to facilitate data democratization and the delivery of data as a product. Data intelligence provides a holistic view of how, when, and why data is produced and consumed across an enterprise, and by whom. This information can be used by data teams toensure business users and data analysts are provided with self-service access to data that is pertinent to their roles and requirements. Delivering data as a product...
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Topics:
Analytics,
Data Ops,
data operations,
AI & Machine Learning,
data platforms,
Analytics & Data,
GenAI,
Data Intelligence
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,
AI,
data operations,
AI & Machine Learning,
data platforms,
Analytics & Data,
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,
AI & Machine Learning,
Analytics & Data,
Data Intelligence,
Data Products,
Data Democratization
Cloud computing has had an enormous impact on the analytics and data industry in recent decades, with the on-demand provisioning of computational resources providing new opportunities for enterprises to lower costs and increase efficiency. Two-thirds of participants in Ventana Research’s Data Lakes Dynamic Insightsresearch are using a cloud-based environment as the primary data platform for analytics.
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Topics:
Analytics,
AI,
AI & Machine Learning,
data platforms,
Analytics & Data,
Generative AI,
Data Intelligence
I have previously written about the impact of intelligent operational applications on the requirements for data platforms. Intelligent applications are used to run the business but also deliver personalization, recommendations and other features generated by machine learning and artificial intelligence. As such, they require a combination of operational and analytic processing functionality. The emergence of these intelligent applications does not eradicate the need for separate analysis of...
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Topics:
Analytics,
Artificial intelligence,
AI & Machine Learning,
data platforms,
Analytics & Data,
Generative AI
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,
AI & Machine Learning,
Analytics & Data
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,
AI & Machine Learning,
Analytics & Data
I previously described how Oracle had positioned its database portfolio to address any and all data platform requirements. The caveat to that statement at the time was that any organization wanting to take advantage of the company’s flagship Oracle Autonomous Database could only do so using Oracle Cloud Infrastructure (OCI) cloud computing service, their own datacenter or a hybrid cloud environment. The widespread popularity of Oracle Database and the advanced automation capabilities delivered...
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Topics:
Analytics,
Business Intelligence,
Cloud Computing,
Data Management,
Data,
Digital Technology,
AI & Machine Learning,
Analytics & Data,
analytic data platforms,
Operational Data Platforms
I previously wrote about the challenge facing distributed SQL database providers to avoid becoming pigeonholed as only being suitable for a niche set of requirements. Factors including performance, reliability, security and scalability provide a focal point for new vendors to differentiate from established providers and get a foot in the door with customer accounts. Expanding and retaining those accounts is not necessarily easy, however, especially as general-purpose data platform providers...
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Topics:
Analytics,
Cloud Computing,
Data,
Digital Technology,
AI & Machine Learning,
Analytics & Data,
Streaming Data & Events,
analytic data platforms