Data Science Blog

MARCH 14, 2023

In der Parallelwelt der ITler wurde das Tool und Ökosystem Apache Hadoop quasi mit Big Data beinahe synonym gesetzt. Artificial Intelligence (AI) ersetzt. Big Data tauchte als Buzzword meiner Recherche nach erstmals um das Jahr 2011 relevant in den Medien auf. Big Data wurde zum Business-Sprech der darauffolgenden Jahre.

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Big Data Big Data Apache Hadoop Data Science 147

Flipboard

NOVEMBER 17, 2023

This type of data is often used in ML and artificial intelligence applications. Prior joining AWS, as a Data/Solution Architect he implemented many projects in Big Data domain, including several data lakes in Hadoop ecosystem. Vector data is a type of data that represents a point in a high-dimensional space.

K-nearest Neighbors 170

K-nearest Neighbors AWS Clustering Database 170

Smart Data Collective

AUGUST 28, 2021

Data lakes have become quite popular due to the emerging use of Hadoop, which is an open-source software. Data lakes are mostly useful to data scientists and engineers that require access to unstructured data to build artificial intelligence or machine learning models.

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Data Lakes Data Warehouse ETL Data Scientist 140

Smart Data Collective

AUGUST 26, 2021

Simply put, it involves a diverse array of tech innovations, from artificial intelligence and machine learning to the internet of things (IoT) and wireless communication networks. Hadoop has also helped considerably with weather forecasting. These data-driven predictions also tend to be surprisingly accurate.

Analytics 133

Analytics Analytics Big Data Analytics Big Data Analytics 133

Pickl AI

OCTOBER 27, 2024

Are you aiming for a role as a Data Analyst, Machine Learning engineer, or perhaps a Data Scientist specialising in Artificial Intelligence? Big Data Technologies: Familiarity with tools like Hadoop and Spark is increasingly important. Programming Languages: Proficiency in programming languages like Python or R is crucial.

Data Science 52

Data Science Data Scientist Machine Learning Machine Learning 52

Pickl AI

DECEMBER 25, 2024

Big data platforms such as Apache Hadoop and Spark help handle massive datasets efficiently. Common Job Titles in Data Science Data Science delves into predictive modeling, artificial intelligence, and machine learning. They must also stay updated on tools such as TensorFlow, Hadoop, and cloud-based platforms like AWS or Azure.

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Data Science Analytics Analytics Data Scientist 52

Analytics Vidhya

JUNE 27, 2020

Overview There are a plethora of data science tools out there – which one should you pick up? Here’s a list of over 20. The post 22 Widely Used Data Science and Machine Learning Tools in 2020 appeared first on Analytics Vidhya.

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Data Science Dojo

JULY 3, 2024

Big Data Technologies : Handling and processing large datasets using tools like Hadoop, Spark, and cloud platforms such as AWS and Google Cloud. Artificial Intelligence : Concepts of AI include neural networks, natural language processing (NLP), and reinforcement learning.

Data Science 150

Data Science Machine Learning Machine Learning Data Visualization 150

Towards AI

SEPTEMBER 28, 2023

It leverages Apache Hadoop for both storage and processing. Apache Spark: Apache Spark is an open-source data processing framework for processing large datasets in a distributed manner. It does in-memory computations to analyze data in real-time. select: Projects a… Read the full blog for free on Medium.

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Apache Hadoop Hadoop Python SQL 75

Becoming Human

JANUARY 23, 2023

So, we know that data science is a process of getting insights from data and helps the business but where this Artificial Intelligence (AI) lies? After understanding data science let’s discuss the second concern “ Data Science vs AI ”.

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Data Science Big Data Big Data Deep Learning 105

ODSC - Open Data Science

APRIL 28, 2023

Due to the tsunami of data available to organizations today, artificial intelligence (AI) and machine learning (ML) are increasingly important to businesses seeking competitive advantage through digital transformation. Editor’s note: Tendü Yoğurtçu, PhD is a speaker for ODSC East 2023 this May 9th-11th.

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ML ML Data Silos Data Quality 98

Smart Data Collective

AUGUST 9, 2023

Those who have massive notes or snippets files would probably like something non-relational such as a Hadoop-based solution. Read Up on Machine Learning Before Deploying It Artificial intelligence-based revenue analysis technology can provide deep insights into how different revenue streams could be improved.

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Analytics Analytics Database Data Analysis 98

IBM Journey to AI blog

MARCH 21, 2024

Artificial intelligence (AI) is revolutionizing industries by enabling advanced analytics, automation and personalized experiences. Leveraging distributed storage and processing frameworks such as Apache Hadoop, Spark or Dask accelerates data ingestion, transformation and analysis.

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Apache Hadoop AI AI Natural Language Processing 79

Smart Data Collective

OCTOBER 28, 2019

Like other terms such as big data or artificial intelligence, APM is capturing the attention of business leaders and innovators, not just for its mysterious “newness”, but also for its ability to preserve company performance and limit disaster. Where are APM Tools Used?

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Big Data Big Data Data Mining Data Mining 85

Smart Data Collective

JULY 25, 2019

Not long ago, big data was one of the most talked about tech trends , as was artificial intelligence (AI). Both of those companies use Hadoop to help clients manage and assess their data, and they were constant competitors. It combines elements of both technologies. In 2014, Cloudera and Hortonworks had much-hyped IPOs.

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Big Data Big Data AI AI 107

Pickl AI

JANUARY 13, 2025

Introduction The field of Artificial Intelligence (AI) is rapidly evolving, and with it, the job market in India is witnessing a seismic shift. Top 10 AI Jobs in India The field of Artificial Intelligence (AI) continues to expand, creating a variety of job opportunities. million by 2027.

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AI AI Machine Learning Machine Learning 52

Pickl AI

SEPTEMBER 17, 2024

This section will highlight key tools such as Apache Hadoop, Spark, and various NoSQL databases that facilitate efficient Big Data management. Apache Hadoop Hadoop is an open-source framework that allows for distributed storage and processing of large datasets across clusters of computers using simple programming models.

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Big Data Big Data Big Data Analytics Big Data Analytics 52

Analytics Vidhya

APRIL 25, 2023

Introduction Since India gained independence, we have always emphasized the importance of elections to make decisions. Seventeen Lok Sabha Elections and over four hundred state legislative assembly elections have been held in India. Earlier, political campaigns used to be conducted through rallies, public speeches, and door-to-door canvassing.

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AI AI Analytics Analytics 306

IBM Journey to AI blog

SEPTEMBER 19, 2023

Overview: Data science vs data analytics Think of data science as the overarching umbrella that covers a wide range of tasks performed to find patterns in large datasets, structure data for use, train machine learning models and develop artificial intelligence (AI) applications.

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Data Science Analytics Analytics Data Scientist 94

Pickl AI

AUGUST 9, 2024

Some of the most notable technologies include: Hadoop An open-source framework that allows for distributed storage and processing of large datasets across clusters of computers. It is built on the Hadoop Distributed File System (HDFS) and utilises MapReduce for data processing. Once data is collected, it needs to be stored efficiently.

Big Data 52

Big Data Big Data Big Data Analytics Big Data Analytics 52

Mlearning.ai

JANUARY 28, 2023

With the growth of big data and artificial intelligence, it is important that you have the right tools to help you achieve your goals. Spark: Spark is a popular platform used for big data processing in the Hadoop ecosystem. From Sale Marketing Business 7 Powerful Python ML For Data Science And Machine Learning need to be use.

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Machine Learning Machine Learning Data Science ML 52

Pickl AI

JULY 25, 2023

With expertise in programming languages like Python , Java , SQL, and knowledge of big data technologies like Hadoop and Spark, data engineers optimize pipelines for data scientists and analysts to access valuable insights efficiently. Big Data Technologies: Hadoop, Spark, etc. Big Data Processing: Apache Hadoop, Apache Spark, etc.

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Data Engineering Data Engineer Data Engineering Data Engineering 52

ODSC - Open Data Science

DECEMBER 19, 2023

The field of artificial intelligence is growing rapidly and with it the demand for professionals who have tangible experience in AI and AI-powered tools. The most popular data science tools include Hadoop, Spark, and Hive. A recent study by Gartner predicts that the global AI market will grow from $15.7 billion in 2021 to $331.2

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Data Scientist Machine Learning Machine Learning AI 96

ODSC - Open Data Science

MAY 31, 2023

Commonly used technologies for data storage are the Hadoop Distributed File System (HDFS), Amazon S3, Google Cloud Storage (GCS), or Azure Blob Storage, as well as tools like Apache Hive, Apache Spark, and TensorFlow for data processing and analytics.

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Data Lakes Machine Learning Machine Learning Apache Kafka 131

Smart Data Collective

SEPTEMBER 26, 2019

For instance, technologies like cloud-based analytics and Hadoop helps in storing large data amounts which would otherwise cost a fortune. As it turns out, Artificial Intelligence and Big Data will empower machine learning technology by continuously reiterating and updating the existing data banks. Agile Development.

Big Data 101

Big Data Big Data Database Analytics 101

Pickl AI

SEPTEMBER 24, 2024

Hadoop Ecosystem As one of the largest Hadoop installations globally, Uber uses this open-source framework for storing and processing vast amounts of data efficiently. Apache Spark For real-time data processing and analytics, Uber utilises Apache Spark—a powerful tool that enables fast computations across large datasets.

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Analytics Analytics Machine Learning Machine Learning 52

Smart Data Collective

MAY 8, 2022

With the evolution of technology and the introduction of Hadoop, Big Data analytics have become more accessible. However, the cost of these systems is too high for smaller organizations and can be a big issue when setting up a project.

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Big Data Analytics Big Data Analytics Big Data Big Data 122

Pickl AI

DECEMBER 2, 2024

Processing frameworks like Hadoop enable efficient data analysis across clusters. Distributed File Systems: Technologies such as Hadoop Distributed File System (HDFS) distribute data across multiple machines to ensure fault tolerance and scalability. Data lakes and cloud storage provide scalable solutions for large datasets.

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Big Data Big Data Data Lakes Apache Hadoop 52

Pickl AI

APRIL 18, 2023

Data Science encompasses several other technologies like Artificial Intelligence, Machine Learning and more. Data Science also incorporates several other principles like mathematics, statistics, computer engineering, Artificial Intelligence, and others. Hence, having these skill sets will help you excel professionally.

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Data Science Machine Learning Machine Learning Data Scientist 52

Alation

FEBRUARY 13, 2020

It was probably a surprise to no one that artificial intelligence (AI) took center stage. Zaidi’s vision for the value of machine learning data catalogs closely resembles the data cataloging vision presented by our Cofounder Aaron Kalb at Strata + Hadoop World 2016.

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Machine Learning Machine Learning Analytics Analytics 52

AWS Machine Learning Blog

DECEMBER 18, 2023

Prior joining AWS, as a Data/Solution Architect he implemented many projects in Big Data domain, including several data lakes in Hadoop ecosystem. In his role Igor is working with strategic partners helping them build complex, AWS-optimized architectures. Babu Srinivasan is a Senior Partner Solutions Architect at MongoDB.

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Clustering AWS Database ML 120

ODSC - Open Data Science

SEPTEMBER 27, 2023

Cost-Efficiency By leveraging cost-effective storage solutions like the Hadoop Distributed File System (HDFS) or cloud-based storage, data lakes can handle large-scale data without incurring prohibitive costs. This is particularly advantageous when dealing with exponentially growing data volumes.

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Data Lakes Data Warehouse Database Big Data 98

Smart Data Collective

JUNE 3, 2019

The ability to connect data silos throughout the organization has been a Business Intelligence challenge for years, especially in banks where mergers and acquisitions have generated numerous and costly data silos. Although some banks are already developing pilots with Hadoop and other associated technologies, there is still a long way to go.

Big Data 85

Big Data Big Data Data Silos AI 85

Mlearning.ai

FEBRUARY 22, 2023

This could involve using a distributed file system, such as Hadoop, or a cloud-based storage service, such as Amazon S3. This could involve batch processing or real-time streaming, depending on your needs. Store the data : After ingesting the data, you need to store it somewhere.

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Big Data Big Data Power BI Hadoop 52

AWS Machine Learning Blog

APRIL 19, 2024

The AWS AI/ML services seem to offer the tools, resources, and infrastructure to support this continuous cycle of innovation, application development, adoption, and reinvestment in the field of artificial intelligence and machine learning. Compared to GPT-2, how many more parameters does GPT-3 have? billion) parameters.

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AWS ML ML Database 120

ODSC - Open Data Science

JUNE 7, 2023

Oracle What Oracle offers is a big data service that is a fully managed, automated cloud service that provides enterprise organizations with a cost-effective Hadoop environment. Snowflake Snowflake is a cross-cloud platform that looks to break down data silos.

Data Lakes 52

Data Lakes Azure Data Warehouse Hadoop 52

IBM Journey to AI blog

JULY 6, 2023

Machine learning (ML) is a subset of artificial intelligence (AI) that focuses on learning from what the data science comes up with. Data science solves a business problem by understanding the problem, knowing the data that’s required, and analyzing the data to help solve the real-world problem. What is machine learning?

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