Data Lakes and SQL: A Match Made in Data Heaven
KDnuggets
JANUARY 16, 2023
In this article, we will discuss the benefits of using SQL with a data lake and how it can help organizations unlock the full potential of their data.
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KDnuggets
JANUARY 16, 2023
In this article, we will discuss the benefits of using SQL with a data lake and how it can help organizations unlock the full potential of their data.
KDnuggets
JUNE 27, 2022
If your raw data is in a SQL-based data lake, why spend the time and money to export the data into a new platform for data prep?
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Dataversity
MARCH 26, 2024
Writing data to an AWS data lake and retrieving it to populate an AWS RDS MS SQL database involves several AWS services and a sequence of steps for data transfer and transformation. This process leverages AWS S3 for the data lake storage, AWS Glue for ETL operations, and AWS Lambda for orchestration.
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Hacker News
MARCH 28, 2024
A unified SQL query interface and portable runtime to locally materialize, accelerate, and query data tables sourced from any database, data warehouse, or data lake. spiceai/spiceai
KDnuggets
JANUARY 18, 2023
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ODSC - Open Data Science
SEPTEMBER 27, 2023
In the ever-evolving world of big data, managing vast amounts of information efficiently has become a critical challenge for businesses across the globe. As data lakes gain prominence as a preferred solution for storing and processing enormous datasets, the need for effective data version control mechanisms becomes increasingly evident.
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.
ODSC - Open Data Science
SEPTEMBER 29, 2023
Data management problems can also lead to data silos; disparate collections of databases that don’t communicate with each other, leading to flawed analysis based on incomplete or incorrect datasets. One way to address this is to implement a data lake: a large and complex database of diverse datasets all stored in their original format.
Data Science Blog
MAY 15, 2023
tl;dr Ein Data Lakehouse ist eine moderne Datenarchitektur, die die Vorteile eines Data Lake und eines Data Warehouse kombiniert. Die Definition eines Data Lakehouse Ein Data Lakehouse ist eine moderne Datenspeicher- und -verarbeitungsarchitektur, die die Vorteile von Data Lakes und Data Warehouses vereint.
Data Science Dojo
JANUARY 12, 2023
When it comes to data, there are two main types: data lakes and data warehouses. What is a data lake? An enormous amount of raw data is stored in its original format in a data lake until it is required for analytics applications. Which one is right for your business?
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.
Dataversity
MARCH 12, 2021
blog series, we experiment with the most interesting blends of data and tools. Whether it’s mixing traditional sources with modern data lakes, open-source devops on the cloud with protected internal legacy tools, SQL with noSQL, web-wisdom-of-the-crowd with in-house handwritten notes, or IoT […].
ODSC - Open Data Science
SEPTEMBER 12, 2023
Although setting up a database to run your analyses may seem like an arduous task, modern open-source time series databases can provide significant benefits to any scientist running time series analysis on a large data set — and with much less effort than you might imagine.
Data Science Dojo
JULY 6, 2023
It offers extensibility and integration with various data engineering tools. dbt (Data Build Tool): dbt is an open-source data transformation and modeling tool. It allows data engineers to build, test, and maintain data pipelines in a version-controlled manner.
phData
APRIL 29, 2024
Oracle – The Oracle connector, a database-type connector, enables real-time data transfer of large volumes of data from on-premises or cloud sources to the destination of choice, such as a cloud data lake or data warehouse.
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.
Dataversity
JULY 9, 2021
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Dataversity
MAY 7, 2021
blog series, we experiment with the most interesting blends of data and tools. Whether it’s mixing traditional sources with modern data lakes, open-source DevOps on the cloud with protected internal legacy tools, SQL with noSQL, web-wisdom-of-the-crowd with in-house handwritten notes, or IoT […].
Smart Data Collective
FEBRUARY 23, 2022
Traditional relational databases provide certain benefits, but they are not suitable to handle big and various data. That is when data lake products started gaining popularity, and since then, more companies introduced lake solutions as part of their data infrastructure. Athena is serverless and managed by AWS.
Dataversity
FEBRUARY 2, 2022
blog series, we experiment with the most interesting blends of data and tools. In the “Will They Blend?”
SAS Software
NOVEMBER 29, 2023
Azure Data Lake Storage (ADLS) Gen2のストレージアカウントの作成 3-2.ストレージアカウントのデータストレージコンテナの作成 Azure SynapseのSQLデータベースをSASライブラリとして定義 4-3.Azure Bulkload機能について 3.BULKLOAD機能を利用するためのAzure側で必要なサービスの作成 BULKLOAD機能を利用するためのAzure側で必要なサービスの作成 3-1.Azure ストレージアカウントのデータストレージコンテナの作成 3-3.ストレージアカウントの利用ユーザー権限の設定 ストレージアカウントの利用ユーザー権限の設定 3-4.データ書き込み用のSASコードの実行
Data Science 101
NOVEMBER 11, 2019
Azure Synapse Analytics This is the future of data warehousing. It combines data warehousing and data lakes into a simple query interface for a simple and fast analytics service. SQL Server 2019 SQL Server 2019 went Generally Available.
Pickl AI
NOVEMBER 15, 2023
Discover the nuanced dissimilarities between Data Lakes and Data Warehouses. Data management in the digital age has become a crucial aspect of businesses, and two prominent concepts in this realm are Data Lakes and Data Warehouses. It acts as a repository for storing all the data.
Mlearning.ai
JUNE 19, 2023
How you now anonymize Data more easily Photo by Dušan veverkolog on Unsplash Google has just announced the public preview of BigQuery differential privacy with SQL building blocks. You can use these functions to anonymize their data. Hence, with this feature you can also ensure that data is shared there securely.
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.
Data Science 101
NOVEMBER 7, 2019
Azure Synapse Analytics can be seen as a merge of Azure SQL Data Warehouse and Azure Data Lake. Synapse allows one to use SQL to query petabytes of data, both relational and non-relational, with amazing speed. Azure Synapse. I think this announcement will have a very large and immediate impact.
phData
SEPTEMBER 26, 2023
Sources The sources involved could influence or determine the options available for the data ingestion tool(s). These could include other databases, data lakes, SaaS applications (e.g. Data flows from the current data platform to the destination. The necessary access is granted so data flows without issue.
AWS Machine Learning Blog
FEBRUARY 28, 2024
Structured Query Language (SQL) is a complex language that requires an understanding of databases and metadata. Today, generative AI can enable people without SQL knowledge. This generative AI task is called text-to-SQL, which generates SQL queries from natural language processing (NLP) and converts text into semantically correct SQL.
AWS Machine Learning Blog
JUNE 13, 2023
The natural language capabilities allow non-technical users to query data through conversational English rather than complex SQL. The AI and language models must identify the appropriate data sources, generate effective SQL queries, and produce coherent responses with embedded results at scale.
The MLOps Blog
JANUARY 23, 2023
These tools may have their own versioning system, which can be difficult to integrate with a broader data version control system. For instance, our data lake could contain a variety of relational and non-relational databases, files in different formats, and data stored using different cloud providers. DVC Git LFS neptune.ai
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.
Pickl AI
APRIL 6, 2023
Data Warehousing concepts and knowledge should be strong. Having experience using at least one end-to-end Azure data lake project. Strong skills in working with Azure cloud-based environment with delta lake implementation. Hands-on experience working with SQLDW and SQL-DB. What is Polybase?
ODSC - Open Data Science
APRIL 3, 2023
Data analysts often must go out and find their data, process it, clean it, and get it ready for analysis. This pushes into Big Data as well, as many companies now have significant amounts of data and large data lakes that need analyzing. Cloud Services: Google Cloud Platform, AWS, Azure.
ODSC - Open Data Science
FEBRUARY 2, 2023
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ODSC - Open Data Science
AUGUST 24, 2023
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Alation
OCTOBER 7, 2021
By viewing data spatially, inferences can be made, and the imagination can be sparked. But in a world where so much data has a location, it’s essential to think spatially. From an ancient lake to a data lake: A paleo perspective. I’ve been getting my hands dirty with data for a long time now.
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. Check a few of them out here.
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.
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. The specific strategy supported depends on your choice of adapter.
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.
ODSC - Open Data Science
JUNE 12, 2023
Power BI Datamarts provide no-code/low-code datamart capabilities using Azure SQL Database technology in the background. The Power BI Datamarts support sensitivity labels, endorsement, discovery, and Row-Level Security ( RLS ), which help protect and manage the data according to the business requirements and compliance needs.
JUNE 26, 2023
Companies are faced with the daunting task of ingesting all this data, cleansing it, and using it to provide outstanding customer experience. Typically, companies ingest data from multiple sources into their data lake to derive valuable insights from the data.
IBM Journey to AI blog
SEPTEMBER 19, 2023
And you should have experience working with big data platforms such as Hadoop or Apache Spark. Additionally, data science requires experience in SQL database coding and an ability to work with unstructured data of various types, such as video, audio, pictures and text.
phData
JULY 10, 2023
Why External Tables are Important Data Ingestion: External tables allow you to easily load data into Snowflake from various external data sources without the need to first stage the data within Snowflake. Data Integration: Snowflake supports seamless integration with other data processing systems and data lakes.
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