Smart Data Collective

SEPTEMBER 25, 2019

Big data has been billed as being the future of business for quite some time. Analysts have found that the market for big data jobs increased 23% between 2014 and 2019. The impact of big data is felt across all sectors of the economy. The data science industry offers various useful computer languages.

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Data Science Blog

JUNE 27, 2023

Kappa – Architecture Jay Kreps introduced the Kappa architecture in 2014 as an alternative to the Lambda architecture. Alternatively, if you seek a streamlined Big Data architecture that excels in handling distinct and continuously emerging events (e.g., The post Big Data – Lambda or Kappa Architecture?

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ODSC - Open Data Science

JANUARY 29, 2024

Thus while crafting clever prompts for chatbots might be part of the picture, the prompt engineer role is far more intricate. They design intricate sequences of prompts, leveraging their knowledge of AI, machine learning, and data science to guide powerful LLMs (Large Language Models) towards complex tasks.

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phData

NOVEMBER 9, 2023

Effectively this is a way to store the source of truth and build (or rebuild) your downstream data products (including data warehouses) from it. What is the Difference Between a Data Lake and a Data Warehouse? Historically, there were big differences.

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AssemblyAI

AUGUST 15, 2023

Around 2012 to 2014, developers proposed updating these modules, but were told to use third party libraries instead. Python for machine learning and data science** In the early 1990s, scientists used Fortran and C++ libraries to solve mathematical problems. However, over time these modules became outdated.

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Alation

SEPTEMBER 28, 2022

DataOps is a set of technologies, processes, and best practices that combine a process-focused perspective on data and the automation methods of the Agile software development methodology to improve speed and quality and foster a collaborative culture of rapid, continuous improvement in the data analytics field. Source: Google Trends.

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Data Science Blog

MARCH 14, 2023

Big Data wurde für viele Unternehmen der traditionellen Industrie zur Enttäuschung, zum falschen Versprechen. Datenqualität hingegen, wurde zum wichtigen Faktor jeder Unternehmensbewertung, was Themen wie Reporting, Data Governance und schließlich dann das Data Engineering mehr noch anschob als die Data Science.

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Data Science Blog

MARCH 19, 2024

So gelingt BI-Teams echte Datendemokratisierung und sie können mit ML-Modellen experimentieren, ohne dabei auf Support von ihren Data-Science-Teams angewiesen zu sei. Ziel der Unternehmen ist es, ihre Datensilos aufzubrechen – oft haben Data Science Teams viele Jahre lang in Silos gearbeitet.

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Data Science Blog

JULY 9, 2024

Espresso AI ist leistungsstark und benutzerfreundlich, sodass auch Teammitglieder ohne tiefgehende Data-Science-Kenntnisse mit neuen Technologien experimentieren und leistungsfähige Modelle entwickeln können. Über Exasol-CEO Martin Golombek Mathias Golombek ist seit Januar 2014 Mitglied des Vorstands der Exasol AG.

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