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        David Menninger's Analyst Perspectives

        We are happy to share some insights about Information Builders’ WebFOCUS Business Intelligence and Analytics Platform drawn from our latest Value Index research, which assesses how well vendors’ offerings meet buyers’ requirements.

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        Topics: business intelligence, embedded analytics, Analytics, Collaboration, Data Governance, Data Preparation, Information Management, Data, AI and Machine Learning

        We are happy to share some insights about MicroStrategy drawn from our latest Value Index research, which assesses how well vendors’ offerings meet buyers’ requirements.

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        Topics: business intelligence, embedded analytics, Analytics, Collaboration, Data Governance, Data Preparation, Information Management, Data, natural language processing, AI and Machine Learning

        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. Alation’s new federated authentication enables users to query cloud services such as Amazon Web Services, Snowflake, Tableau and more, using a single sign-on. The release also includes a Search application programming interface that allows for the integration of Alation...

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        Topics: Analytics, Business Intelligence, Collaboration, Data Preparation, Data, Information Management (IM), AI and Machine Learning

        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. Data quality efforts are focused on clean data. Yes, clean data is important. but so is bad data. To be more accurate, the original data as recorded by an organization’s various devices and systems is important.

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        Topics: Data Governance, Data Preparation, Information Management, Data, data lakes

        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 challenges organizations face in applying ML. Traditional ML model development is resource-intensive, requiring significant domain knowledge and time to produce and compare dozens of models. And as the number of ML models grow, their management becomes...

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        Topics: business intelligence, embedded analytics, Analytics, Collaboration, Data Governance, Data Preparation, Data, AI and Machine Learning

        The amount of data flowing into organizations is growing exponentially, creating a need to process more data more quickly than ever before. Our Data Preparation Benchmark Research shows that accessing and preparing data continues to be the most time-consuming part of making data available for analysis. This can potentially slow down the organizational functions which depend on the analysis results. Trying to get ahead of the backlog with incremental improvements to existing approaches and...

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        Topics: business intelligence, embedded analytics, Analytics, Collaboration, Data Governance, Data Preparation, Data, Information Management (IM), data lakes

        Organizations are accelerating their digital transformation and looking for innovative ways to engage with customers in this new digital era of data management. The goal is to understand how to manage the growing volume of data in real time, across all sources and platforms, and use it to inform, streamline and transform internal operations. Over the years, the adoption of cloud computing has gained momentum with more and more organizations trying to make use of applications, data, analytics...

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        Topics: business intelligence, embedded analytics, Analytics, Collaboration, Data Governance, Data Preparation, Information Management, Internet of Things, Data, natural language processing, data lakes, AI and Machine Learning

        Organizations are increasingly using data as a strategic asset, which makes data services critical. Huge volumes of data need to be stored, managed, discovered and analyzed. Cloud computing and storage approaches provide enterprises with various capabilities to store and process their data in third-party data centers. The advent of data platforms previously discussed here are essential for organizations to effectively manage their data assets.

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        Topics: embedded analytics, Analytics, Business Intelligence, Collaboration, Data Governance, Data Lake, Data Preparation, Data, Microsoft Azure, AI and Machine Learning

        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.

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        Topics: Data Governance, Data Preparation, Information Management, Data, data lakes, Streaming Data, data operations, Event Data, Data catalog, Event Streams, Event Stream Processing

        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. Without data integrity, organizations cannot trust the information produced by their data processes, and will be discouraged from using that data, resulting in inefficiencies and reduced effectiveness.

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        Topics: Analytics, Business Intelligence, Data Governance, Data Preparation, Information Management, Data, data lakes
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        Our Analyst Perspective Policy

        • 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@isg-research.net

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