Analytics Vidhya

OCTOBER 6, 2023

In today’s rapidly evolving digital landscape, seamless data, applications, and device integration are more pressing than ever. Enter Microsoft Fabric, a cutting-edge solution designed to revolutionize how we interact with technology.

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Analytics Analytics Power BI Data Lakes 343

Analytics Vidhya

MARCH 21, 2023

to store and analyze this data to get valuable business insights from it. You will study top 11 azure interview questions in this article which will discuss different data services like Azure Cosmos […] The post Top 11 Azure Data Services Interview Questions in 2023 appeared first on Analytics Vidhya.

Azure 306

Azure Analytics Analytics Data Lakes 306

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. AWS Athena and S3. Limits of Athena.

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Data Lakes AWS SQL Big Data 124

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.

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Data Lakes Clustering Big Data Big Data 52

Alation

FEBRUARY 20, 2020

For many enterprises, a hybrid cloud data lake is no longer a trend, but becoming reality. Due to these needs, hybrid cloud data lakes emerged as a logical middle ground between the two consumption models. Without business context, business users are less likely to use the data lake and insights will be hard to come by.

Data Lakes 52

Data Lakes Cloud Data AWS Tableau 52

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 Scientist 97

Data Scientist Data Lakes Database Data Science 97

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 […].

Data Lakes 52

Data Lakes SQL Database Data Science 52

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.

Database 101

Database SQL AWS AI 101

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 […].

Data Lakes 52

Data Lakes SQL Database Data Science 52

Dataversity

FEBRUARY 2, 2022

blog series, we experiment with the most interesting blends of data and tools. In the “Will They Blend?”

Data Lakes 52

Data Lakes SQL Analytics Analytics 52

Dataversity

JULY 9, 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 […].

Azure 52

Azure Data Lakes SQL ML 52

ODSC - Open Data Science

FEBRUARY 24, 2023

While machine learning frameworks and platforms like PyTorch, TensorFlow, and scikit-learn can perform data exploration well, it’s not their primary intent. There are also plenty of data visualization libraries available that can handle exploration like Plotly, matplotlib, D3, Apache ECharts, Bokeh, etc.

Exploratory Data Analysis 126

Exploratory Data Analysis Data Visualization Data Analysis Data Analysis 126

ODSC - Open Data Science

FEBRUARY 2, 2023

Computer Science and Computer Engineering Similar to knowing statistics and math, a data scientist should know the fundamentals of computer science as well. While knowing Python, R, and SQL are expected, you’ll need to go beyond that. Big Data As datasets become larger and more complex, knowing how to work with them will be key.

Data Science 98

Data Science Data Scientist Computer Science Computer Science 98

Pickl AI

APRIL 21, 2025

Introduction In today’s hyper-connected world, you hear the terms “Big Data” and “Data Science” thrown around constantly. They pop up in news articles, job descriptions, and tech discussions. What exactly is Big Data? Database Knowledge: Like SQL for retrieving data.

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Big Data Big Data Data Science Machine Learning 52

IBM Journey to AI blog

JANUARY 18, 2023

In another decade, the internet and mobile started the generate data of unforeseen volume, variety and velocity. It required a different data platform solution. Hence, Data Lake emerged, which handles unstructured and structured data with huge volume. This article endeavors to alleviate those confusions.

Data Lakes 52

Data Lakes Data Warehouse Azure Apache Hadoop 52

IBM Journey to AI blog

AUGUST 4, 2023

When workers get their hands on the right data, it not only gives them what they need to solve problems, but also prompts them to ask, “What else can I do with data?” ” through a truly data literate organization. What is data democratization?

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Data Lakes AI AI Data Governance 73

The MLOps Blog

JANUARY 23, 2023

As data is the foundation of any machine learning project, it is essential to have a system in place for tracking and managing changes to data over time. However, data versioning control is frequently given little attention, leading to issues such as data inconsistencies and the inability to reproduce results.

ML 52

ML ML Data Lakes Machine Learning 52

ODSC - Open Data Science

AUGUST 24, 2023

Bayesian Customer Lifetime Values Modeling using PyMC3 This article is all about implementing BG-NBD, a probabilistic hierarchical model, using PyMC3 to analyze customer purchase behavior. That’s why enriching your analysis with trusted, fit-for-use, third-party data is key to ensuring long-term success.

Data Lakes 52

Data Lakes Data Science Machine Learning Machine Learning 52

phData

MARCH 22, 2024

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. amazonaws.com") spark.conf.set("spark.hadoop.fs.s3a.endpoint.region", os.environ['AWS_REGION']) Access Iceberg tables using spark and spark sql.

SQL 52

SQL AWS Database Data Lakes 52

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.

Analytics 52

Analytics Analytics Data Analyst Data Science 52

How to Learn Machine Learning

MAY 2, 2025

Best Practices for Azure Machine Learning Projects To get the most out of Azure Machine Learning, consider these best practices: Data Management Use Azure Data Stores : Connect to various data sources including Azure Blob Storage, Azure Data Lake, and Azure SQL Database for efficient data access.

Azure 52

Azure Machine Learning Machine Learning Data Science 52

ODSC - Open Data Science

MARCH 30, 2023

Using Azure ML to Train a Serengeti Data Model, Fast Option Pricing with DL, and How To Connect a GPU to a Container Using Azure ML to Train a Serengeti Data Model for Animal Identification In this article, we will cover how you can train a model using Notebooks in Azure Machine Learning Studio. Check a few of them out here.

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Azure ML ML Data Modeling 52

ODSC - Open Data Science

JUNE 12, 2023

The Datamarts capability opens endless possibilities for organizations to achieve their data analytics goals on the Power BI platform. This article is an excerpt from the book Expert Data Modeling with Power BI, Third Edition by Soheil Bakhshi, a completely updated and revised edition of the bestselling guide to Power BI and data modeling.

Power BI 52

Power BI Data Warehouse ETL Data Preparation 52

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. Originally posted on OpenDataScience.com Read more data science articles on OpenDataScience.com , including tutorials and guides from beginner to advanced levels!

Apache Kafka 52

Apache Kafka Machine Learning Machine Learning Data Science 52

Pickl AI

NOVEMBER 4, 2024

The global Big Data and Data Engineering Services market, valued at USD 51,761.6 This article explores the key fundamentals of Data Engineering, highlighting its significance and providing a roadmap for professionals seeking to excel in this vital field. SQL SQL is crucial for querying and managing relational databases.

Data Engineering 52

Data Engineering Data Engineering Data Engineer Data Engineering 52

The MLOps Blog

OCTOBER 20, 2023

Nevertheless, many data scientists will agree that they can be really valuable – if used well. And that’s what we’re going to focus on in this article, which is the second in my series on Software Patterns for Data Science & ML Engineering. in a pandas DataFrame) but in the company’s data warehouse (e.g.,

SQL 52

SQL Data Scientist Database Python 52

ODSC - Open Data Science

APRIL 24, 2023

To cluster the data we have to calculate distances between IPs — The number of all possible IP pairs is very large, and we had to solve the scale problem. Data Processing and Clustering Our data is stored in a Data Lake and we used PrestoDB as a query engine. AS ip_1, r.ip AND l.ip < r.ip

Clustering 52

Clustering SQL Algorithm Data Science 52

Alation

FEBRUARY 20, 2020

While others will catalog your data, only Alation continues to innovate on how collaboration can change the very nature of your analysis. I’ll be there with the Alation team sharing our product and discussing how we can partner with you to drive data literacy in your organization.

Data Lakes 52

Data Lakes Data Analyst Analytics Analytics 52

Alation

JULY 19, 2022

Modern data catalogs surface a wide range of data asset types. For instance, Alation can return wiki-like articles, conversations, and business intelligence objects, in addition to traditional tables. Increasingly, data catalogs not only provide the location of data assets, but also the means to retrieve them.

Data Scientist 59

Data Scientist Data Quality Data Science Data Analyst 59

The MLOps Blog

JUNE 27, 2023

To provide you with a comprehensive overview, this article explores the key players in the MLOps and FMOps (or LLMOps) ecosystems, encompassing both open-source and closed-source tools, with a focus on highlighting their key features and contributions. Check out the documentation to get started.

Machine Learning 134

Machine Learning Machine Learning ML ML 134

Mlearning.ai

JULY 10, 2023

Click here for link to Part 1 of this article Continuing the Beginner’s Guide to GCP BigQuery series; in Part 2, we will take a look at the advantages and use cases of key features in BigQuery. To create a Scheduled Query, the initial step is to ensure your SQL is accurately entered in the Query Editor.

SQL 52

SQL Database Database Administration Data Lakes 52

IBM Journey to AI blog

JULY 17, 2023

sales conversation summaries, insurance coverage, meeting transcripts, contract information) Generate: Generate text content for a specific purpose, such as marketing campaigns, job descriptions, blogs or articles, and email drafting support.

AI 74

AI AI Machine Learning Machine Learning 74

AWS Machine Learning Blog

MAY 31, 2024

Select the uploaded file and from Actions dropdown and choose the Query with S3 Select option to query the.csv data using SQL if the data was loaded correctly. In this demonstration, let’s assume that you need to remove the data related to a particular customer. The AWS DPA is incorporated into the AWS Service Terms.

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AWS Machine Learning Machine Learning Database 132

ODSC - Open Data Science

JANUARY 18, 2024

So as you take inventory of your existing skill set, you’ll want to start to identify the areas where you need to focus on to become a data engineer. These areas may include SQL, database design, data warehousing, distributed systems, cloud platforms (AWS, Azure, GCP), and data pipelines. First, articles.

Data Engineering 52

Data Engineering Data Engineering Data Engineer Data Engineering 52

DagsHub

OCTOBER 23, 2024

Managing unstructured data is essential for the success of machine learning (ML) projects. Without structure, data is difficult to analyze and extracting meaningful insights and patterns is challenging. This article will discuss managing unstructured data for AI and ML projects. How to properly manage unstructured data.

Machine Learning 52

Machine Learning Machine Learning Data Lakes AI 52

Pickl AI

OCTOBER 17, 2024

It involves extracting data from various sources, transforming it into a suitable format, and loading it into a target system for analysis and reporting. As organisations increasingly rely on data-driven insights, effective ETL processes ensure data integrity and quality, enabling informed decision-making.

ETL 52

ETL Data Warehouse Data Quality SQL 52

Mlearning.ai

FEBRUARY 16, 2023

In this article, you’ll discover what a Snowflake data warehouse is, its pros and cons, and how to employ it efficiently. The platform enables quick, flexible, and convenient options for storing, processing, and analyzing data. Data warehousing is a vital constituent of any business intelligence operation.

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Data Warehouse Business Intelligence Business Intelligence Database 52