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        Matt Aslett's Analyst Perspectives

        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 distributed-edge processing infrastructure. As we recently noted, as compute and storage are distributed across a hybrid and multi-cloud architecture, so, too, is the data it stores and relies upon. This presents challenges for organizations to...

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        Topics: business intelligence, Analytics, Data Governance, Data, data operations, AI & Machine Learning, data platforms

        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 based on the breadth and depth of functionality offered by NoSQL database providers today, which has expanded the range of use cases for which NoSQL databases are potentially viable. There remain a significant number of organizations that have not...

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        Topics: NoSQL, Data, data platforms, Use Cases

        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 affiliated, open-source database projects, several commercial NoSQL database providers are now established as credible alternatives to the various relational database providers, while all the major cloud providers and relational database giants now also...

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        Topics: Analytics, Data, AI & Machine Learning, data platforms

        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 structured data processing and analytics acceleration capabilities are the equivalent of turbines, generators and transformers in a hydroelectric power station. While these capabilities are more typically associated with data warehousing, they are now...

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        Topics: Analytics, Data Governance, Data Integration, Data, data lakes, data operations, AI & Machine Learning, data platforms, Streaming Data & Events

        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 those that are incapable of seeing or responding to the need for change. Data-driven organizations stand to gain competitive advantage, responding faster to worker and customer demands for more innovative, data-rich applications and personalized...

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        Topics: business intelligence, Analytics, Data Integration, Data, data lakes, data operations, AI & Machine Learning, data platforms, Streaming Data & Events

        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 to maximize data to operate with greater efficiency, while operational data platforms are designed to store, manage and process data to support worker-, customer- and partner-facing operational applications. At the same time, however, we see...

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        Topics: embedded analytics, Analytics, Business Intelligence, Data, Digital Technology, AI & Machine Learning, data platforms, Analytics & Data, Streaming Data & Events, Natural Data

        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.

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        Topics: Data Governance, Data Integration, Data, data lakes, data operations, data platforms, Streaming Data & Events

        The term NoSQL has been a misnomer ever since it appeared in 2009 to describe a group of emerging databases. It was true that a lack of support for Structured Query Language (SQL) was common to the various databases referred to as NoSQL. However, it was always one of a number of common characteristics, including flexible schema, distributed data processing, open source licensing, and the use of non-relational data models (key value, document, graph) rather than relational tables. As the various...

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        Topics: Business Continuity, Analytics, Data, Digital Technology, digital business, data platforms

        Data lakes have enormous potential as a source of business intelligence. However, many early adopters of data lakes have found that simply storing large amounts of data in a data lake environment is not enough to generate business intelligence from that data. Similarly, lakes and reservoirs have enormous potential as sources of energy. However, simply storing large amounts of water in a lake is not enough to generate energy from that water. A hydroelectric power station is required to harness...

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        Topics: Analytics, Business Intelligence, Cloud Computing, Data Governance, Data Integration, Data, Digital Technology, data lakes, data operations, AI & Machine Learning, data platforms

        As I noted when joining Ventana Research, the range of options faced by organizations in relation to data processing and analytics can be bewildering. When it comes to data platforms, however, there is one fundamental consideration that comes before all others: Is the workload primarily operational or analytic? Although most database products can be used for operational or analytic workloads, the market has been segmented between products targeting operational workloads, and those targeting...

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        Topics: Analytics, Business Intelligence, Data, data lakes, data operations, AI & Machine Learning, data platforms
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        • Ventana Research’s Analyst Perspectives are fact-based analysis and guidance on business, industry and technology vendor trends. Each Analyst Perspective presents the view of the analyst who is an established subject matter expert on new developments, business and technology trends, findings from our research, or best practice insights.

          Each is prepared and reviewed in accordance with Ventana Research’s strict standards for accuracy and objectivity and reviewed to ensure it delivers reliable and actionable insights. It is reviewed and edited by research management and is approved by the Chief Research Officer; no individual or organization outside of Ventana Research reviews any Analyst Perspective before it is published. If you have any issue with an Analyst Perspective, please email them to ChiefResearchOfficer@ventanaresearch.com

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