AWS Machine Learning Blog

AUGUST 21, 2023

You can streamline the process of feature engineering and data preparation with SageMaker Data Wrangler and finish each stage of the data preparation workflow (including data selection, purification, exploration, visualization, and processing at scale) within a single visual interface.

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phData

NOVEMBER 8, 2024

Note : Cloud Data warehouses like Snowflake and Big Query already have a default time travel feature. However, this feature becomes an absolute must-have if you are operating your analytics on top of your data lake or lakehouse. It can also be integrated into major data platforms like Snowflake. Contact phData Today!

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ODSC - Open Data Science

APRIL 24, 2023

Botnet Detection at Scale — Lessons Learned From Clustering Billions of Web Attacks Into Botnets Editor’s note: Ori Nakar is a speaker for ODSC Europe this June. Be sure to check out his talk, “ Botnet detection at scale — Lesson learned from clustering billions of web attacks into botnets ,” there! AS ip_1, r.ip AND l.ip < r.ip

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Flipboard

AUGUST 17, 2023

Amazon Redshift uses SQL to analyze structured and semi-structured data across data warehouses, operational databases, and data lakes, using AWS-designed hardware and ML to deliver the best price-performance at any scale. Here we use RedshiftDatasetDefinition to retrieve the dataset from the Redshift cluster.

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Tableau

JUNE 8, 2021

Domain experts, for example, feel they are still overly reliant on core IT to access the data assets they need to make effective business decisions. In all of these conversations there is a sense of inertia: Data warehouses and data lakes feel cumbersome and data pipelines just aren't agile enough.

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Women in Big Data

NOVEMBER 27, 2024

Its PostgreSQL foundation ensures compatibility with most SQL clients. Architecture At its core, Redshift consists of clusters made up of compute nodes, coordinated by a leader node that manages communications, parses queries, and executes plans by distributing tasks to the compute nodes.

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Snorkel AI

MAY 26, 2023

[link] Ahmad Khan, head of artificial intelligence and machine learning strategy at Snowflake gave a presentation entitled “Scalable SQL + Python ML Pipelines in the Cloud” about his company’s Snowpark service at Snorkel AI’s Future of Data-Centric AI virtual conference in August 2022. Welcome everybody.

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Snorkel AI

MAY 26, 2023

[link] Ahmad Khan, head of artificial intelligence and machine learning strategy at Snowflake gave a presentation entitled “Scalable SQL + Python ML Pipelines in the Cloud” about his company’s Snowpark service at Snorkel AI’s Future of Data-Centric AI virtual conference in August 2022. Welcome everybody.

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phData

DECEMBER 4, 2023

Thirty seconds is a good default for human users; if you find that queries are regularly queueing, consider making your warehouse a multi-cluster that scales on-demand. Cluster Count If your warehouse has to serve many concurrent requests, you may need to increase the cluster count to meet demand.

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Pickl AI

JULY 6, 2023

Hive is a data warehousing infrastructure built on top of Hadoop. It has the following features: It facilitates querying, summarizing, and analyzing large datasets Hadoop also provides a SQL-like language called HiveQL Hive allows users to write queries to extract valuable insights from structured and semi-structured data stored in Hadoop.

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phData

MARCH 22, 2024

Snowflake-managed Iceberg table’s performance is at par with Snowflake native tables while storing the data in public cloud storage. They are Ideal for situations where the data is already stored in data lakes and do not intend to load into Snowflake but need to use the features and performance of Snowflake.

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phData

NOVEMBER 6, 2023

Example: models: my_project: events: # materialize all models in models/events as tables +materialized: table csvs: # this is redundant, and does not need to be set +materialized: view We can also configure the materialization type inside the dbt SQL file or the yaml file. You can do this by providing either of the following.

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ODSC - Open Data Science

JULY 22, 2023

We had bigger sessions on getting started with machine learning or SQL, up to advanced topics in NLP, and how to make deepfakes. Here are some highlights from ODSC Europe 2023, including some pictures of speakers and attendees, popular talks, and a summary of what kept people busy.

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Pickl AI

NOVEMBER 4, 2024

Role of Data Engineers in the Data Ecosystem Data Engineers play a crucial role in the data ecosystem by bridging the gap between raw data and actionable insights. They are responsible for building and maintaining data architectures, which include databases, data warehouses, and data lakes.

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Pickl AI

JANUARY 28, 2025

This involves several key processes: Extract, Transform, Load (ETL): The ETL process extracts data from different sources, transforms it into a suitable format by cleaning and enriching it, and then loads it into a data warehouse or data lake. Data Lakes: These store raw, unprocessed data in its original format.

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Pickl AI

AUGUST 9, 2024

Big Data Technologies and Tools A comprehensive syllabus should introduce students to the key technologies and tools used in Big Data analytics. 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.

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phData

FEBRUARY 5, 2024

Setting up the Information Architecture Setting up an information architecture during migration to Snowflake poses challenges due to the need to align existing data structures, types, and sources with Snowflake’s multi-cluster, multi-tier architecture. Essentially, it functions like Google Translate — but for SQL dialects.

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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. Data warehousing is a vital constituent of any business intelligence operation.

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The MLOps Blog

JUNE 27, 2023

It provides tools and components to facilitate end-to-end ML workflows, including data preprocessing, training, serving, and monitoring. Kubeflow integrates with popular ML frameworks, supports versioning and collaboration, and simplifies the deployment and management of ML pipelines on Kubernetes clusters.

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DagsHub

OCTOBER 23, 2024

Here’s the structured equivalent of this same data in tabular form: With structured data, you can use query languages like SQL to extract and interpret information. In contrast, such traditional query languages struggle to interpret unstructured data. This text has a lot of information, but it is not structured.

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The MLOps Blog

MARCH 15, 2023

Data Processing : You need to save the processed data through computations such as aggregation, filtering and sorting. Data Storage : To store this processed data to retrieve it over time – be it a data warehouse or a data lake. Uses secure protocols for data security.

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Flipboard

DECEMBER 4, 2024

The use of separate data warehouses and lakes has created data silos, leading to problems such as lack of interoperability, duplicate governance efforts, complex architectures, and slower time to value. You can use Amazon SageMaker Lakehouse to achieve unified access to data in both data warehouses and data lakes.

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IBM Journey to AI blog

JULY 5, 2023

Data Lakes have been around for well over a decade now, supporting the analytic operations of some of the largest world corporations. Such data volumes are not easy to move, migrate or modernize. The challenges of a monolithic data lake architecture Data lakes are, at a high level, single repositories of data at scale.

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IBM Journey to AI blog

SEPTEMBER 25, 2023

Every day, millions of riders use the Uber app, unwittingly contributing to a complex web of data-driven decisions. This blog takes you on a journey into the world of Uber’s analytics and the critical role that Presto, the open source SQL query engine, plays in driving their success. What is Presto?

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phData

SEPTEMBER 20, 2023

Snowpark is the set of libraries and runtimes in Snowflake that securely deploy and process non-SQL code, including Python , Java, and Scala. As a declarative language, SQL is very powerful in allowing users from all backgrounds to ask questions about data. What is Snowflake’s Snowpark? Why Does Snowpark Matter?

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The MLOps Blog

MARCH 21, 2023

Orchestrators are concerned with lower-level abstractions like machines, instances, clusters, service-level grouping, replication, and so on. Along with the schedulers, they are integral to managing the regular workflows your data scientists run and how the tasks in those workflows communicate with the ML platform.

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Alation

JULY 18, 2022

A simple model to control access to data via a UI or SQL. Automatically tracking data lineage across queries executed in any language. To ensure you can deliver on this world-changing vision of data, Alation helps you maximize the value of your data lake with integrations to the Unity catalog. and much more!

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Pickl AI

FEBRUARY 23, 2025

Apache Hadoop Apache Hadoop is an open-source framework that allows for distributed storage and processing of large datasets across clusters of computers using simple programming models. Key Features : Scalability : Hadoop can handle petabytes of data by adding more nodes to the cluster. Statistics Kafka handles over 1.1

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The MLOps Blog

JUNE 5, 2023

One of the hardest things about MLOps today is that a lot of data scientists aren’t native software engineers, but it may be possible to lower the bar to software engineering. Environments that can’t have a GPU – you can’t carry a cluster around in your phone or whatever it is, or wherever you are to do everything.

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AWS Machine Learning Blog

OCTOBER 11, 2024

These models support mapping different data types like text, images, audio, and video into the same vector space to enable multi-modal queries and analysis. Because it’s serverless, it removes the operational complexities of provisioning, configuring, and tuning your OpenSearch clusters.

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