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I Am Done Using Visual Studio!

Paul Turley

for BI data model development. For several years, Visual Studio has been my go-to tool for designing semantic data models used for Business Intelligent reporting. In 2012 when Microsoft began the transition from on-disk cubes to in-memory SSAS Tabular models, I used SQL Server Data Tools (SSDT) to create tabular models.

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The Rise of Unstructured Data

Cloudera

For example, the number of hyperscale centres is reported to have doubled between 2015 and 2020. In other words, structured data has a pre-defined data model , whereas unstructured data doesn’t. . Similar figures of 80% of data being unstructured and growing at a rate of 55% to 65% annually is reported here. Zettabytes per year.

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Rising Tide Rents and Robber Baron Rents

O'Reilly on Data

By the end of 2012, it was up to 82%. Some of those innovations, like Amazon’s cloud computing business, represented enormous new markets and a new business model. Google, for example, invented the Large Language model architecture that underlies today’s disruptive AI startups. The market was maturing.

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Perform time series forecasting using Amazon Redshift ML and Amazon Forecast

AWS Big Data

Amazon Redshift ML makes it easy for data analysts and database developers to create, train, and apply machine learning (ML) models using familiar SQL commands in Amazon Redshift. Simply use SQL statements to create and train SageMaker ML models using your Redshift data and then use these models to make predictions.

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Challenges in replacing SSRS with Microsoft Power BI

BizAcuity

There are several reporting tools and platforms available today, and enterprises usually choose the one that is best suited for their business needs. Two popular options for reporting platforms are SQL Server Reporting Services (SSRS) and Microsoft Power BI. It is an intensified tool compared to other crystal reports.

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Leveraging generative AI on AWS to transform life sciences

IBM Big Data Hub

The industry is under tremendous pressure to accelerate drug development at an optimal cost, automate time- and labor-intensive tasks like document or report creation to preserve employee morale, and accelerate delivery. Yet, it is burdened by long R&D cycles and labor-intensive clinical, manufacturing and compliancy regimens.

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4 hidden risks of your enterprise cloud strategy

CIO Business Intelligence

When performing whatever minimal due diligence the cloud platform permits — SOC reports, GDPR compliance, PCI ROC, etc. The US Commerce Department in January, for example, proposed a rule banning Chinese companies from training their LLM models in US cloud environments. That’s where the contract comes into play.

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