ODSC - Open Data Science

OCTOBER 15, 2023

Cloudera Cloudera is a cloud-based platform that provides businesses with the tools they need to manage and analyze data. They offer a variety of services, including data warehousing, data lakes, and machine learning. The platform includes several features that make it easy to develop and test data pipelines.

Machine Learning 52

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Alation

MAY 16, 2023

But with the sheer amount of data continually increasing, how can a business make sense of it? Robust data pipelines. What is a Data Pipeline? A data pipeline is a series of processing steps that move data from its source to its destination. The answer?

Data Pipeline 69

Data Pipeline Data Governance Data Lakes Data Warehouse 69

Dataconomy

FEBRUARY 23, 2023

Data engineers play a crucial role in managing and processing big data. They are responsible for designing, building, and maintaining the infrastructure and tools needed to manage and process large volumes of data effectively. What is data engineering?

Data Engineering 91

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Alation

MARCH 22, 2022

Accenture calls it the Intelligent Data Foundation (IDF), and it’s used by dozens of enterprises with very complex data landscapes and analytic requirements. Simply put, IDF standardizes data engineering processes. How the IDF Supports a Smarter Data Pipeline. Take a look at figure 1 below.

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ODSC - Open Data Science

FEBRUARY 2, 2023

Big data isn’t an abstract concept anymore, as so much data comes from social media, healthcare data, and customer records, so knowing how to parse all of that is needed. This pushes into big data as well, as many companies now have significant amounts of data and large data lakes that need analyzing.

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IBM Journey to AI blog

JANUARY 5, 2023

The first generation of data architectures represented by enterprise data warehouse and business intelligence platforms were characterized by thousands of ETL jobs, tables, and reports that only a small group of specialized data engineers understood, resulting in an under-realized positive impact on the business.

Data Quality 52

Data Quality Data Lakes Data Warehouse Business Intelligence 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 Engineer Data Engineering Data Engineering 52

Alation

MAY 16, 2023

But with the sheer amount of data continually increasing, how can a business make sense of it? Robust data pipelines. What is a Data Pipeline? A data pipeline is a series of processing steps that move data from its source to its destination. The answer?

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Data Pipeline Data Governance Data Lakes Data Warehouse 40

ODSC - Open Data Science

FEBRUARY 15, 2024

We couldn’t be more excited to announce the first sessions for our second annual Data Engineering Summit , co-located with ODSC East this April. Join us for 2 days of talks and panels from leading experts and data engineering pioneers. Is Gen AI A Data Engineering or Software Engineering Problem?

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52

IBM Journey to AI blog

SEPTEMBER 19, 2023

By analyzing datasets, data scientists can better understand their potential use in an algorithm or machine learning model. The data science lifecycle Data science is iterative, meaning data scientists form hypotheses and experiment to see if a desired outcome can be achieved using available data.

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Data Science Analytics Analytics Data Scientist 85

The MLOps Blog

MAY 17, 2023

This article explores the importance of ETL pipelines in machine learning, a hands-on example of building ETL pipelines with a popular tool, and suggests the best ways for data engineers to enhance and sustain their pipelines. What is an ETL data pipeline in ML?

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Alation

APRIL 18, 2023

This, in turn, helps them to build new data pipelines, solutions, and products, or clean up the data that’s there. It bears mentioning data profiling has evolved tremendously. Modern data profiling will also gather all the potential problems in one quick scan. Data migration Digital transformation is ongoing.

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Data Profiling Data Quality Data Governance Data Pipeline 52

IBM Journey to AI blog

OCTOBER 16, 2023

How to scale AL and ML with built-in governance A fit-for-purpose data store built on an open lakehouse architecture allows you to scale AI and ML while providing built-in governance tools. A data store lets a business connect existing data with new data and discover new insights with real-time analytics and business intelligence.

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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 Wrangling Data Scientist 52

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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Mlearning.ai

FEBRUARY 16, 2023

Thus, the solution allows for scaling data workloads independently from one another and seamlessly handling data warehousing, data lakes , data sharing, and engineering. Simplify and Win Experienced data engineers value simplicity. What will You Attain with Snowflake?

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Data Warehouse Business Intelligence Business Intelligence Database 52

phData

FEBRUARY 14, 2023

Source data formats can only be Parquer, JSON, or Delimited Text (CSV, TSV, etc.). Streamsets Data Collector StreamSets Data Collector Engine is an easy-to-use data pipeline engine for streaming, CDC, and batch ingestion from any source to any destination. The biggest reason is the ease of use.

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Data Warehouse Azure AWS Database 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

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Machine Learning Machine Learning ML ML 134

Alation

JUNE 21, 2022

Why start with a data source and build a visualization, if you can just find a visualization that already exists, complete with metadata about it? Data scientists went beyond database tables to data lakes and cloud data stores. Data scientists want to catalog not just information sources, but models.

DataOps 52

DataOps Data Scientist Data Quality Data Pipeline 52

phData

DECEMBER 4, 2023

If you answer “yes” to any of these questions, you will need cloud storage, such as Amazon AWS’s S3, Azure Data Lake Storage or GCP’s Google Storage. Data Pipelines “Data pipeline” means moving data in a consistent, secure, and reliable way at some frequency that meets your requirements.

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Clustering Database SQL Data Pipeline 98

Flipboard

NOVEMBER 24, 2023

JuMa is tightly integrated with a range of BMW Central IT services, including identity and access management, roles and rights management, BMW Cloud Data Hub (BMW’s data lake on AWS) and on-premises databases. He works closely with enterprise customers to design data platforms and build advanced analytics and ML use cases.

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ML ML AWS AI 95

phData

FEBRUARY 24, 2023

Organizations can unite their siloed data and securely share governed data while executing diverse analytic workloads. Snowflake’s engine provides a solution for data warehousing, data lakes, data engineering, data science, data application development, and data sharing.

Analytics 52

Analytics Analytics Database Python 52

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. programs in Information Science and Data Analytics.

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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.

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AI AI Machine Learning Machine Learning 68

Snorkel AI

MAY 26, 2023

What’s really important in the before part is having production-grade machine learning data pipelines that can feed your model training and inference processes. And that’s really key for taking data science experiments into production. Let’s go and talk about machine learning pipelining.

SQL 52

SQL ML ML Python 52

Snorkel AI

MAY 26, 2023

What’s really important in the before part is having production-grade machine learning data pipelines that can feed your model training and inference processes. And that’s really key for taking data science experiments into production. Let’s go and talk about machine learning pipelining.

SQL 52

SQL ML ML Python 52

Mlearning.ai

JULY 10, 2023

Without partitioning, daily data activities will cost your company a fortune and a moment will come where the cost advantage of GCP BigQuery becomes questionable. By keeping the data in cloud storage instead of native BigQuery tables, you can reduce your storage costs while maintaining the ability to query the data.

SQL 52

SQL Database Database Administration Data Lakes 52

phData

NOVEMBER 9, 2023

A data warehouse is a centralized and structured storage system that enables organizations to efficiently store, manage, and analyze large volumes of data for business intelligence and reporting purposes. What is a Data Lake? What is the Difference Between a Data Lake and a Data Warehouse?

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The MLOps Blog

MARCH 21, 2023

Other users Some other users you may encounter include: Data engineers , if the data platform is not particularly separate from the ML platform. Analytics engineers and data analysts , if you need to integrate third-party business intelligence tools and the data platform, is not separate. Allegro.io

Machine Learning 69

Machine Learning Machine Learning Data Scientist ML 69

IBM Journey to AI blog

JULY 27, 2023

Powering a knowledge management system with a data lakehouse Organizations need a data lakehouse to target data challenges that come with deploying an AI-powered knowledge management system. It provides the combination of data lake flexibility and data warehouse performance to help to scale AI.

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AI AI Data Scientist Data Quality 60

Alation

FEBRUARY 17, 2023

I suggest building out a RACI framework that assigns core activities across these key roles: (1) Data Owner; (2) Business Data Steward; (3) Technical (IT) Data Steward; (4) Enterprise Data Steward; (5) Data Engineer; and (6) Data Consumer. Communication is essential. Where do you govern?

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DataRobot Blog

OCTOBER 3, 2017

Enterprise data architects, data engineers, and business leaders from around the globe gathered in New York last week for the 3-day Strata Data Conference , which featured new technologies, innovations, and many collaborative ideas. 2) When data becomes information, many (incremental) use cases surface.

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