Flipboard

DECEMBER 11, 2024

Many of these applications are complex to build because they require collaboration across teams and the integration of data, tools, and services. Data engineers use data warehouses, data lakes, and analytics tools to load, transform, clean, and aggregate data. Big Data Architect.

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SQL AWS Data Lakes ML 158

phData

SEPTEMBER 19, 2023

With the amount of data companies are using growing to unprecedented levels, organizations are grappling with the challenge of efficiently managing and deriving insights from these vast volumes of structured and unstructured data. What is a Data Lake? Consistency of data throughout the data lake.

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Data Lakes Data Modeling Data Models Data Warehouse 52

phData

NOVEMBER 8, 2024

Data Versioning and Time Travel Open Table Formats empower users with time travel capabilities, allowing them to access previous dataset versions. Versioning also ensures a safer experimentation environment, where data scientists can test new models or hypotheses on historical data snapshots without impacting live data.

Data Lakes 52

Data Lakes Data Warehouse Database Azure 52

AWS Machine Learning Blog

FEBRUARY 21, 2025

Despite the benefits of this architecture, Rocket faced challenges that limited its effectiveness: Accessibility limitations: The data lake was stored in HDFS and only accessible from the Hadoop environment, hindering integration with other data sources. This also led to a backlog of data that needed to be ingested.

Data Science 70

Data Science AWS Hadoop Data Scientist 70

Pickl AI

NOVEMBER 4, 2024

Summary: The fundamentals of Data Engineering encompass essential practices like data modelling, warehousing, pipelines, and integration. Understanding these concepts enables professionals to build robust systems that facilitate effective data management and insightful analysis. What is Data Engineering?

Data Engineering 52

Data Engineering Data Engineering Data Engineer Data Engineering 52

Pickl AI

APRIL 6, 2023

Accordingly, one of the most demanding roles is that of Azure Data Engineer Jobs that you might be interested in. The following blog will help you know about the Azure Data Engineering Job Description, salary, and certification course. How to Become an Azure Data Engineer?

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Azure Data Engineering Data Engineering Data Engineer 52

ODSC - Open Data Science

JANUARY 18, 2024

Data engineering is a rapidly growing field, and there is a high demand for skilled data engineers. If you are a data scientist, you may be wondering if you can transition into data engineering. In this blog post, we will discuss how you can become a data engineer if you are a data scientist.

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Data Engineering Data Engineering Data Engineer Data Engineering 52

ODSC - Open Data Science

JANUARY 30, 2024

Data engineering is a hot topic in the AI industry right now. And as data’s complexity and volume grow, its importance across industries will only become more noticeable. But what exactly do data engineers do? So let’s do a quick overview of the job of data engineer, and maybe you might find a new interest.

Data Engineering 52

Data Engineering Data Engineering Data Engineer Data Engineering 52

ODSC - Open Data Science

FEBRUARY 2, 2023

The role of a data scientist is in demand and 2023 will be no exception. To get a better grip on those changes we reviewed over 25,000 data scientist job descriptions from that past year to find out what employers are looking for in 2023. Data Science Of course, a data scientist should know data science!

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Data Science Data Scientist Computer Science Computer Science 98

Pickl AI

SEPTEMBER 5, 2024

Summary: This blog provides a comprehensive roadmap for aspiring Azure Data Scientists, outlining the essential skills, certifications, and steps to build a successful career in Data Science using Microsoft Azure. This roadmap aims to guide aspiring Azure Data Scientists through the essential steps to build a successful career.

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Azure Data Scientist Data Science Machine Learning 52

Pickl AI

AUGUST 1, 2023

Aspiring and experienced Data Engineers alike can benefit from a curated list of books covering essential concepts and practical techniques. These 10 Best Data Engineering Books for beginners encompass a range of topics, from foundational principles to advanced data processing methods. What is Data Engineering?

Data Engineering 52

Data Engineering Data Engineering Data Engineer Data Engineering 52

ODSC - Open Data Science

DECEMBER 19, 2023

Data Scientist Data scientists are responsible for developing and implementing AI models. They use their knowledge of statistics, mathematics, and programming to analyze data and identify patterns that can be used to improve business processes. The average salary for a data scientist is $112,400 per year.

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Data Scientist Machine Learning Machine Learning Computer Science 96

Data Science Blog

MARCH 3, 2023

Übrigens nicht mehr so stark bei den Data Scientists, auch wenn richtig gute Mitarbeiter ebenfalls rar gesät sind, den größten Bedarf haben Unternehmen eher bei den Data Engineers. Das sind die Kollegen, die die Data Warehouses oder Data Lakes aufbauen und pflegen.

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Data Warehouse Data Lakes Data Engineering Data Engineer 147

Flipboard

NOVEMBER 24, 2023

In an increasingly digital and rapidly changing world, BMW Group’s business and product development strategies rely heavily on data-driven decision-making. With that, the need for data scientists and machine learning (ML) engineers has grown significantly. JuMa automatically provisions a new AWS account for the workspace.

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ML ML AWS Data Scientist 151

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.

Data Science 94

Data Science Analytics Analytics Data Scientist 94

Alation

JULY 19, 2022

These days, data scientists are in high demand. Across the country, data scientists have an unemployment rate of 2% and command an average salary of nearly $100,000. For these reasons, finding and evaluating data is often time-consuming. How Data Catalogs Help Data Scientists Ask Better Questions.

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Data Scientist Data Quality Data Science Data Analyst 59

The MLOps Blog

JUNE 27, 2023

Alignment to other tools in the organization’s tech stack Consider how well the MLOps tool integrates with your existing tools and workflows, such as data sources, data engineering platforms, code repositories, CI/CD pipelines, monitoring systems, etc. For example, neptune.ai Check out the Kubeflow documentation.

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Machine Learning Machine Learning ML ML 134

AWS Machine Learning Blog

SEPTEMBER 1, 2023

These teams are as follows: Advanced analytics team (data lake and data mesh) – Data engineers are responsible for preparing and ingesting data from multiple sources, building ETL (extract, transform, and load) pipelines to curate and catalog the data, and prepare the necessary historical data for the ML use cases.

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AI AI ML ML 124

Tableau

FEBRUARY 14, 2022

“I think one of the most important things I see people do right, is to make sure that you build the data foundation from the ground up correctly,” said Ali Ghodsi, CEO of Databricks. The data lakehouse is one such architecture—with “lake” from data lake and “house” from data warehouse.

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AI AI Tableau Data Scientist 98

Tableau

FEBRUARY 14, 2022

“I think one of the most important things I see people do right, is to make sure that you build the data foundation from the ground up correctly,” said Ali Ghodsi, CEO of Databricks. The data lakehouse is one such architecture—with “lake” from data lake and “house” from data warehouse.

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AI AI Tableau Data Scientist 95

AWS Machine Learning Blog

DECEMBER 7, 2023

Fatma Nur Dumlupınar Keşir received her Bachelor’s Degree from Industrial Engineering Department at Boğaziçi University. She then joined Getir in 2022 as a data scientist and has worked on Recommendation Engine projects, Mathematical Programming for Workforce Planning.

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AWS Algorithm Data Science Machine Learning 124

AWS Machine Learning Blog

FEBRUARY 7, 2025

In this post, we assign the functions in terms of the ML lifecycle to each role as follows: Lead data scientist Provision accounts for ML development teams, govern access to the accounts and resources, and promote standardized model development and approval process to eliminate repeated engineering effort.

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ML ML Data Scientist AWS 62

AWS Machine Learning Blog

FEBRUARY 13, 2024

Let’s demystify this using the following personas and a real-world analogy: Data and ML engineers (owners and producers) – They lay the groundwork by feeding data into the feature store Data scientists (consumers) – They extract and utilize this data to craft their models Data engineers serve as architects sketching the initial blueprint.

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AWS ML ML Machine Learning 126

AWS Machine Learning Blog

MAY 15, 2023

His team is responsible for designing, implementing, and maintaining end-to-end machine learning algorithms and data-driven solutions for Getir. Mutlu Polatcan is a Staff Data Engineer at Getir, specializing in designing and building cloud-native data platforms. He loves combining open-source projects with cloud services.

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Algorithm Data Scientist Machine Learning Machine Learning 85

Alation

JUNE 21, 2022

The audience grew to include data scientists (who were even more scarce and expensive) and their supporting resources (e.g., After that came data governance , privacy, and compliance staff. Power business users and other non-purely-analytic data citizens came after that. Data engineers want to catalog data pipelines.

DataOps 52

DataOps Data Scientist Data Quality Data Pipeline 52

The MLOps Blog

JANUARY 23, 2023

But, it is not rare that data engineers and database administrators process, control, and store terabytes of data in projects that are not related to machine learning. When it comes to data complexity, it is for sure that in machine learning, we are dealing with much more complex data. DVC Git LFS neptune.ai

ML 52

ML ML Data Lakes Machine Learning 52

AWS Machine Learning Blog

DECEMBER 18, 2023

By using these capabilities, businesses can efficiently store, manage, and analyze time-series data, enabling data-driven decisions and gaining a competitive edge. Prior joining AWS, as a Data/Solution Architect he implemented many projects in Big Data domain, including several data lakes in Hadoop ecosystem.

Clustering 121

Clustering AWS Database ML 121

ODSC - Open Data Science

MARCH 30, 2023

5 Reasons Why SQL is Still the Most Accessible Language for New Data Scientists Between its ability to perform data analysis and ease-of-use, here are 5 reasons why SQL is still ideal for new data scientists to get into the field. But there’s a problem: how on earth do you hook up that GPU?

Azure 52

Azure ML ML Data Modeling 52

AWS Machine Learning Blog

JUNE 20, 2024

Our goal was to improve the user experience of an existing application used to explore the counters and insights data. The data is stored in a data lake and retrieved by SQL using Amazon Athena. Millions of counters are added daily, together with 20 million insights updated daily to spot threat patterns.

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SQL Database AWS Machine Learning 106

Alation

JULY 7, 2022

To answer these questions we need to look at how data roles within the job market have evolved, and how academic programs have changed to meet new workforce demands. In the 2010s, the growing scope of the data landscape gave rise to a new profession: the data scientist. The data scientist.

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Data Scientist Data Analyst Analytics Analytics 52

ODSC - Open Data Science

OCTOBER 3, 2024

From October 29th to 31st, we’ve curated a schedule packed with over 150 hands-on workshops and expert-led talks designed to help you sharpen your skills and elevate your role as a data scientist or AI professional. Apply now for a chance to participate, and we’ll be in touch if space is available.

Data Science 40

Data Science Data Lakes Data Scientist AI 40

IBM Journey to AI blog

JULY 17, 2023

Within watsonx.ai, users can take advantage of open-source frameworks like PyTorch, TensorFlow and scikit-learn alongside IBM’s entire machine learning and data science toolkit and its ecosystem tools for code-based and visual data science capabilities.

AI 74

AI AI Machine Learning Machine Learning 74

Alation

FEBRUARY 13, 2020

Expansion in our business model is driven by the number of users of the data catalog, which means that our average customer is virally successful relative to their initial investment. The Alation Data Catalog is taking years of data lake and self-service analytics investments and driving them from investments to insights.

Data Lakes 52

Data Lakes Analytics Analytics Machine Learning 52

ODSC - Open Data Science

NOVEMBER 19, 2024

Despite the rise of big data technologies and cloud computing, the principles of dimensional modeling remain relevant. This session delved into how these traditional techniques have adapted to data lakes and real-time analytics, emphasizing their enduring importance for building scalable, efficient data systems.

Deep Learning 52

Deep Learning Deep Learning Data Science AI 52

ODSC - Open Data Science

OCTOBER 20, 2023

HPCC Systems — The Kit and Kaboodle for Big Data and Data Science Bob Foreman | Software Engineering Lead | LexisNexis/HPCC Join this session to learn how ECL can help you create powerful data queries through a comprehensive and dedicated data lake platform.

AI 52

AI AI Data Science Machine Learning 52

IBM Journey to AI blog

DECEMBER 16, 2022

For example, data catalogs have evolved to deliver governance capabilities like managing data quality and data privacy and compliance. It uses metadata and data management tools to organize all data assets within your organization.

Data Quality 52

Data Quality Data Governance Data Scientist Data Wrangling 52

IBM Journey to AI blog

MARCH 14, 2024

With newfound support for open formats such as Parquet and Apache Iceberg, Netezza enables data engineers, data scientists and data analysts to share data and run complex workloads without duplicating or performing additional ETL.

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AWS Database ETL AI 93