Data Science Dojo

SEPTEMBER 11, 2024

With this full-fledged solution, you don’t have to spend all your time and effort combining different services or duplicating data. Overview of One Lake Fabric features a lake-centric architecture, with a central repository known as OneLake. On the home page, select Synapse Data Engineering.

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Power BI Data Pipeline Data Warehouse Data Engineering 337

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?

Big Data 91

Big Data Big Data Data Engineering Data Engineering 91

Dataconomy

JUNE 1, 2023

Unified data storage : Fabric’s centralized data lake, Microsoft OneLake, eliminates data silos and provides a unified storage system, simplifying data access and retrieval. OneLake is designed to store a single copy of data in a unified location, leveraging the open-source Apache Parquet format.

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Power BI Data Lakes Azure Data Silos 194

AWS Machine Learning Blog

AUGUST 8, 2024

Data is the foundational layer for all generative AI and ML applications. Managing and retrieving the right information can be complex, especially for data analysts working with large data lakes and complex SQL queries. The following diagram illustrates the solution architecture.

SQL 125

SQL Data Lakes Data Analyst AWS 125

Flipboard

MAY 14, 2025

In this post, we show you how Amazon Q Business can help augment your generative AI needs in all the abovementioned use cases and more by answering questions, providing summaries, generating content, and securely completing tasks based on data and information in your enterprise systems. Traditionally, businesses face a challenge.

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ODSC - Open Data Science

JUNE 7, 2023

To make your data management processes easier, here’s a primer on data lakes, and our picks for a few data lake vendors worth considering. What is a data lake? First, a data lake is a centralized repository that allows users or an organization to store and analyze large volumes of data.

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Data Lakes Azure Data Warehouse Hadoop 52

AWS Machine Learning Blog

FEBRUARY 21, 2025

While these models are trained on vast amounts of generic data, they often lack the organization-specific context and up-to-date information needed for accurate responses in business settings. After ingesting the data, you create an agent with specific instructions: agent_instruction = """You are the Amazon Bedrock Agent.

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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 Models Data Modeling Data Warehouse 52

Alation

FEBRUARY 20, 2020

When it was no longer a hard requirement that a physical data model be created upon the ingestion of data, there was a resulting drop in richness of the description and consistency of the data stored in Hadoop. You did not have to understand or prepare the data to get it into Hadoop, so people rarely did.

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Data Lakes Hadoop Tableau Big Data 52

AWS Machine Learning Blog

APRIL 3, 2025

Data is one of the most critical assets of many organizations. Theyre constantly seeking ways to use their vast amounts of information to gain competitive advantages. Amazon AppFlow was used to facilitate the smooth and secure transfer of data from various sources into ODAP.

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phData

APRIL 4, 2023

Fivetran today announced support for Amazon Simple Storage Service (Amazon S3) with Apache Iceberg data lake format. Amazon S3 is an object storage service from Amazon Web Services (AWS) that offers industry-leading scalability, data availability, security, and performance.

Data Lakes 52

Data Lakes Data Warehouse Cloud Data Data Science 52

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?

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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.

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Data Engineering Data Engineering Data Engineering Data Engineer 52

AWS Machine Learning Blog

OCTOBER 20, 2023

Data and governance foundations – This function uses a data mesh architecture for setting up and operating the data lake, central feature store, and data governance foundations to enable fine-grained data access. This framework considers multiple personas and services to govern the ML lifecycle at scale.

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phData

SEPTEMBER 29, 2023

When you think of data engineering , what comes to mind? In reality, though, if you use data (read: any information), you are most likely practicing some form of data engineering every single day. Said differently, any tools or steps we use to help us utilize data can be considered data engineering.

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Data Engineering Data Engineering Data Engineering Data Engineer 52

AWS Machine Learning Blog

MARCH 1, 2023

It helps you extract information by recognizing sentiments, key phrases, entities, and much more, allowing you to take advantage of state-of-the-art models and adapt them for your specific use case. MLOps requires the integration of software development, operations, data engineering, and data science.

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Data Lakes AWS ML ML 98

phData

NOVEMBER 9, 2023

The main goal of a data mesh structure is to drive: Domain-driven ownership Data as a product Self-service infrastructure Federated governance One of the primary challenges that organizations face is data governance. What is a Data Lake? What is the Difference Between a Data Lake and a Data Warehouse?

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Alation

JANUARY 26, 2023

Many users struggle to access the information they need or understand its full context once that access is unlocked. What’s worse, just 3% of the data in a business enterprise meets quality standards. There’s also no denying that data management is becoming more important, especially to the public.

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Data Governance Data Engineering Data Engineering Data Engineering 52

AWS Machine Learning Blog

JUNE 5, 2023

Many teams are turning to Athena to enable interactive querying and analyze their data in the respective data stores without creating multiple data copies. Athena allows applications to use standard SQL to query massive amounts of data on an S3 data lake. Create a data lake with Lake Formation.

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Machine Learning Machine Learning AWS Data Lakes 96

Flipboard

NOVEMBER 17, 2023

The vector field should be represented as an array of numbers (BSON int32, int64, or double data types only). Refer to Review knnVector Type Limitations for more information about the limitations of the knnVector type. As a Data Engineer he was involved in applying AI/ML to fraud detection and office automation.

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K-nearest Neighbors AWS Clustering Database 168

Alation

FEBRUARY 13, 2020

Andreas Kohlmaier, Head of Data Engineering at Munich Re 1. --> Ron Powell, independent analyst and industry expert for the BeyeNETWORK and executive producer of The World Transformed FastForward Series, interviews Andreas Kohlmaier, Head of Data Engineering at Munich Re. But it is a little hard to consume.

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Data Lakes Analytics Analytics Data Engineering 52

ODSC - Open Data Science

MAY 16, 2023

Data Mesh More data management systems in 2023 will also shift toward a data mesh architecture. This decentralized architecture breaks data lakes into smaller domains specific to a given team or department. However, enabling these architectures safely will require careful planning and security.

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Database Data Science Data Lakes Data Observability 98

Women in Big Data

OCTOBER 9, 2024

With the explosive growth of big data over the past decade and the daily surge in data volumes, it’s essential to have a resilient system to manage the vast influx of information without failures. The success of any data initiative hinges on the robustness and flexibility of its big data pipeline.

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Big Data Big Data Apache Kafka Data Pipeline 59

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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Data Science Data Scientist Computer Science Computer Science 98

phData

NOVEMBER 1, 2024

Quotes It's extremely important because many of the Gen AI and LLM applications take an unstructured data approach, meaning many of the tools require you to give the tools full access to your data in an unrestricted way and let it crawl and parse it completely. Data governance is the only way to ensure those requirements are met.

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Data Governance Data Quality ML ML 52

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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Data Lakes Azure Data Pipeline Hadoop 52

AWS Machine Learning Blog

FEBRUARY 21, 2025

Thats why we use advanced technology and data analytics to streamline every step of the homeownership experience, from application to closing. This also led to a backlog of data that needed to be ingested. Lake Formation makes this data available to both the build and compute accounts.

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Data Science AWS Hadoop Data Scientist 74

AWS Machine Learning Blog

JUNE 18, 2024

Through evaluations of sensors and informed decision-making support, Afri-SET empowers governments and civil society for effective air quality management. The attempt is disadvantaged by the current focus on data cleaning, diverting valuable skills away from building ML models for sensor calibration.

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AWS Machine Learning Blog

DECEMBER 18, 2023

By exploring these challenges, organizations can recognize the importance of real-time forecasting and explore innovative solutions to overcome these hurdles, enabling them to stay competitive, make informed decisions, and thrive in today’s fast-paced business environment. For more information, refer to the following resources.

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Clustering AWS Database ML 121

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. Each document holds an example question and information about it.

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SQL Database AWS Machine Learning 112

AWS Machine Learning Blog

AUGUST 15, 2024

With over 50 connectors, an intuitive Chat for data prep interface, and petabyte support, SageMaker Canvas provides a scalable, low-code/no-code (LCNC) ML solution for handling real-world, enterprise use cases. Organizations often struggle to extract meaningful insights and value from their ever-growing volume of data.

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ML ML Data Preparation AWS 124

AWS Machine Learning Blog

DECEMBER 7, 2023

Historic transactional demand data, location-based weather information, holiday dates, promotions and marketing campaign data are the features used in the model as shown in the graph below. He joined Getir in 2022 as a Data Scientist and started working on time-series forecasting and mathematical optimization projects.

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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

IBM Journey to AI blog

SEPTEMBER 19, 2023

To pursue a data science career, you need a deep understanding and expansive knowledge of machine learning and AI. Data scientists will typically perform data analytics when collecting, cleaning and evaluating data. Watsonx comprises of three powerful components: the watsonx.ai

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Data Science Analytics Analytics Data Scientist 94

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.

AI 95

AI AI Tableau Data Scientist 95

DagsHub

OCTOBER 23, 2024

How to leverage Generative AI to manage unstructured data Benefits of applying proper unstructured data management processes to your AI/ML project. What is Unstructured Data? One thing is clear : unstructured data doesn’t mean it lacks information.

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Machine Learning Machine Learning Data Lakes AI 52

Flipboard

NOVEMBER 24, 2023

With that, the need for data scientists and machine learning (ML) engineers has grown significantly. These skilled professionals are tasked with building and deploying models that improve the quality and efficiency of BMW’s business processes and enable informed leadership decisions.

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ML ML AWS AI 148