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Five Modern Data Architecture Trends

David Menninger's Analyst Perspectives

I was recently asked to identify key modern data architecture trends. Data architectures have changed significantly to accommodate larger volumes of data as well as new types of data such as streaming and unstructured data. Here are some of the trends I see continuing to impact data architectures.

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Critical Components of Big Data Architecture for a Translation Company

Smart Data Collective

Big data technology has been instrumental in helping organizations translate between different languages. We covered the benefits of using machine learning and other big data tools in translations in the past. How Does Big Data Architecture Fit with a Translation Company?

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The Difference Between Data Architecture and Enterprise Architecture

erwin

Although there is some crossover, there are stark differences between data architecture and enterprise architecture (EA). That’s because data architecture is actually an offshoot of enterprise architecture. The Value of Data Architecture. Data Architecture and Data Modeling.

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Snowflake Builds on Its Success

David Menninger's Analyst Perspectives

Traditional on-premises data processing solutions have led to a hugely complex and expensive set of data silos where IT spends more time managing the infrastructure than extracting value from the data.

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Big Data Modeling Improves Business Intelligence

TDAN

Through big data modeling, data-driven organizations can better understand and manage the complexities of big data, improve business intelligence (BI), and enable organizations to benefit from actionable insight.

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Converting Big Data into Actionable Intelligence

TDAN

In today’s world, access to data is no longer a problem. There are such huge volumes of data generated in real-time that several businesses don’t know what to do with all of it. Unless big data is converted to actionable insights, there is nothing much an enterprise can do.

Big Data 145
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6 Big Data Mistakes You Must Avoid At All Costs

Smart Data Collective

However, while doing so, you need to work with a lot of data and this could lead to some big data mistakes. But why use data-driven marketing in the first place? When you collect data about your audience and campaigns, you’ll be better placed to understand what works for them and what doesn’t. Using Small Datasets.

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