Forrester IT
SEPTEMBER 28, 2023
The mark of an insight driven business is a data architecture strategy grounded on business outcomes. Unfortunately, investments to modernize data platforms have historically led to solving the challenges, bottlenecks, and objectives of IT.
Forrester IT
SEPTEMBER 8, 2023
Data fabric has been gaining traction in the enterprise.
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Forrester IT
FEBRUARY 23, 2024
I am happy to announce that my coverage area now includes Data Center Services, Infrastructure Outsourcing, and Semiconductors. This is in addition to my existing coverage of Technical Debt and Enterprise Architecture.
IT Toolbox
DECEMBER 13, 2022
A data center houses backend computers (without a user interface) and ancillary systems like cooling and networking. The post What Is a Data Center? Working, Types, Architecture, and Best Practices appeared first on.
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There’s no getting around it: selecting the right foundational data-layer components is crucial for long-term application success.
IT Toolbox
AUGUST 17, 2022
Enterprises can house structured and unstructured data via object storage units or blobs using a data lake. The post What is a Data Lake? Definition, Architecture, Tools, and Applications appeared first on Spiceworks.
IT Toolbox
AUGUST 18, 2022
A data warehouse aggregates enterprise data from multiple sources to support querying and analysis for better decisions. The post What Is a Data Warehouse? Definition, Architecture, Tools, and Applications appeared first on Spiceworks.
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From understanding its distributed architecture to unlocking its incredible power for industries like healthcare, finance, retail and more, experience how Cassandra® can transform your entire data operations.
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Apache Cassandra is an open-source distributed database that boasts an architecture that delivers high scalability, near 100% availability, and powerful read-and-write performance required for many data-heavy use cases.
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In an effort to be data-driven, many organizations are looking to democratize data. However, they often struggle with increasingly larger data volumes, reverting back to bottlenecking data access to manage large numbers of data engineering requests and rising data warehousing costs.
Speaker: Jeremiah Morrow, Nicolò Bidotti, and Achille Barbieri
Data teams in large enterprise organizations are facing greater demand for data to satisfy a wide range of analytic use cases. Yet they are continually challenged with providing access to all of their data across business units, regions, and cloud environments.
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While data platforms, artificial intelligence (AI), machine learning (ML), and programming platforms have evolved to leverage big data and streaming data, the front-end user experience has not kept up. Traditional Business Intelligence (BI) aren’t built for modern data platforms and don’t work on modern architectures.
Speaker: Veena Vasudevan and Jason Hughes
With data stored in vendor-agnostic files and table formats like Apache Iceberg, the open lakehouse is the best architecture to enable data democratization. By moving analytic workloads to the data lakehouse you can save money, make more of your data accessible to consumers faster, and provide users a better experience.
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Data fuels the modern enterprise — today more than ever, businesses compete on their ability to turn big data into essential business insights. Increasingly, enterprises are leveraging cloud data lakes as the platform used to store data for analytics, combined with various compute engines for processing that data.
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An organization’s data is copied for many reasons, namely ingesting datasets into data warehouses, creating performance-optimized copies, and building BI extracts for analysis. Read this whitepaper to learn: Why organizations frequently end up with unnecessary data copies.
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