Cloudyard

DECEMBER 24, 2024

In this blog, well explore Building an ETL Pipeline with Snowpark by simulating a scenario where commerce data flows through distinct data layersRAW, SILVER, and GOLDEN.These tables form the foundation for insightful analytics and robust business intelligence. They need to: Consolidate raw data from orders, customers, and products.

Building 52

Building Raw Data Scala Business Intelligence 52

Engineering at Meta

FEBRUARY 4, 2025

The result of these batch operations in the data warehouse is a set of comma delimited text files containing the unfiltered raw data logs for each user. We do this by passing the raw data through various renderers, discussed in more detail in the next section.

Accessibility 80

Accessibility Accessible Raw Data Data Warehouse 80

Snowflake

JANUARY 29, 2024

Bring your raw Google Analytics data to Snowflake with just a few clicks The Snowflake Connector for Google Analytics makes it a breeze to get your Google Analytics data, either aggregated data or raw data, into your Snowflake account. Here’s a quick guide to get started: 1.

Raw Data 126

Raw Data Aggregated Data Cloud Data 126

Cloudera

MAY 19, 2021

To try and predict this, an extensive dataset including anonymised details on the individual loanee and their historical credit history are included. As a machine learning problem, it is a classification task with tabular data, a perfect fit for RAPIDS. Get the Dataset. The dataset can be downloaded from: [link].

Machine Learning 137

Machine Learning Data Science Datasets Raw Data 137

Rockset

MARCH 27, 2019

The application you're implementing needs to analyze this data, combining it with other datasets, to return live metrics and recommended actions. But how can you interrogate the data and frame your questions correctly if you don't understand the shape of your data? Where do you begin?

Raw Data 40

Raw Data SQL NoSQL Datasets 40

Monte Carlo

JANUARY 29, 2025

But in practice, each team creates their own separate data transformations directly from the raw data. Different data scientists are building different models with totally disconnected datasets. This practice isnt unusual, but it can lead to problems. Theres no easy way to trace issues across the pipeline.

Media 52

Media Data Science Datasets Raw Data 52

Maxime Beauchemin

AUGUST 28, 2017

Traditionalists would suggest starting a data stewardship and ownership program, but at a certain scale and pace, these efforts are a weak force that are no match for the expansion taking place.

Data Engineering 174

Data Engineering Data Engineer Engineering Software Engineer 174

Towards Data Science

FEBRUARY 6, 2024

As you do not want to start your development with uncertainty, you decide to go for the operational raw data directly. Accessing Operational Data I used to connect to views in transactional databases or APIs offered by operational systems to request the raw data. Does it sound familiar?

Systems 98

Systems Raw Data Metadata Data Cleanse 98

Edureka

JANUARY 2, 2025

Additionally, it manages sizable datasets without causing Power BI to crash or perform less quickly. The purpose of the Power BI SUMX function was to perform calculations across a table or dataset row by row. Data about Quantity and the cost price of Amount are included in the dataset (1).

BI 52

BI Datasets Business Intelligence Data Analysis 52

ThoughtSpot

MARCH 5, 2024

When created, Snowflake materializes query results into a persistent table structure that refreshes whenever underlying data changes. These tables provide a centralized location to host both your raw data and transformed datasets optimized for AI-powered analytics with ThoughtSpot.

BI 111

BI Datasets SQL Raw Data 111

Edureka

APRIL 14, 2025

Microsoft offers a leading solution for business intelligence (BI) and data visualization through this platform. It empowers users to build dynamic dashboards and reports, transforming raw data into actionable insights. However, it leans more toward transforming and presenting cleaned data rather than processing raw datasets.

BI 40

BI Business Intelligence Raw Data Retail 40

Precisely

SEPTEMBER 25, 2023

Read our eBook Validation and Enrichment: Harnessing Insights from Raw Data In this ebook, we delve into the crucial data validation and enrichment process, uncovering the challenges organizations face and presenting solutions to simplify and enhance these processes. What perspectives and opportunities could you uncover?

Data Validation 100

Data Validation Process Raw Data Data Cleanse 100

Christophe Blefari

APRIL 21, 2023

Data Engineering at Adyen — "Data engineers at Adyen are responsible for creating high-quality, scalable, reusable and insightful datasets out of large volumes of raw data" This is a good definition of one of the possible responsibilities of DE. Synthetic data are AI generated data.

Raw Data 130

Raw Data Data SQL Datasets 130

Edureka

MARCH 26, 2025

In this article, we will be diving into the world of Data Imputation, discussing its importance and techniques, and also learning about Multiple Imputations. What Is Data Imputation? Data imputation is the method of filling in missing or unavailable information in a dataset with other numbers.

Medical 40

Medical Datasets Data Analysis Machine Learning 40

Precisely

NOVEMBER 20, 2023

We work with organizations around the globe that have diverse needs but can only achieve their objectives with expertly curated data sets containing thousands of different attributes. Enrichment: The Secret to Supercharged AI You’re not just improving accuracy by augmenting your datasets with additional information.

Raw Data 121

Raw Data Insurance Data Portfolio 121

Edureka

MARCH 15, 2025

By learning the details of smaller datasets, they better balance task-specific performance and resource efficiency. It is seamlessly integrated across Meta’s platforms, increasing user access to AI insights, and leverages a larger dataset to enhance its capacity to handle complex tasks. What are Small language models?

Entertainment 74

Entertainment Retail Education Healthcare 74

Towards Data Science

NOVEMBER 16, 2023

Unlike streaming data, which needs instant processing, batch data can be processed at scheduled intervals or when resources become available. Splittable in chunks : instead of processing an entire dataset in a single, resource-intensive operation, batch data can be divided into smaller, more manageable segments.

Data Process 98

Data Process Process Raw Data Data 98

RandomTrees

MARCH 10, 2025

Cloud-Based Solutions: Large datasets may be effectively stored and analysed using cloud platforms. From Information to Insight The difficulty is not gathering data but making sense of it. Tableau, Power BI, and SAS provide user-friendly interfaces and extensive modelling capabilities.

Retail 52

Retail Hospitality Data Governance Banking 52

AltexSoft

MAY 12, 2022

For further steps, you need to load your dataset to Python or switch to a platform specifically focusing on analysis and/or machine learning. Labeling of audio data in Audacity. Source: Towards Data Science. Voice and sound data acquisition. Free data sources. Commercial datasets. Expert datasets.

Machine Learning 122

Machine Learning Building Deep Learning Healthcare 122

Precisely

DECEMBER 13, 2023

Read our eBook Validation and Enrichment: Harnessing Insights from Raw Data In this ebook, we delve into the crucial data validation and enrichment process, uncovering the challenges organizations face and presenting solutions to simplify and enhance these processes.

Raw Data 96

Raw Data Entertainment Data Validation Education 96

Monte Carlo

JULY 30, 2024

Data teams can use uniqueness tests to measure their data uniqueness. Uniqueness tests enable data teams to programmatically identify duplicate records to clean and normalize raw data before entering the production warehouse.

Data Validation 96

Data Validation Datasets Medical Raw Data 96

AltexSoft

AUGUST 25, 2021

You can’t simply feed the system your whole dataset of emails and expect it to understand what you want from it. It’s called deep because it comprises many interconnected layers — the input layers (or synapses to continue with biological analogies) receive data and send it to hidden layers that perform hefty mathematical computations.

Process 139

Process Deep Learning Datasets Machine Learning 139

Data Engineering Podcast

DECEMBER 16, 2019

Summary Building clean datasets with reliable and reproducible ingestion pipelines is completely useless if it’s not possible to find them and understand their provenance. The solution to discoverability and tracking of data lineage is to incorporate a metadata repository into your data platform.

Metadata 100

Metadata PostgreSQL Datasets Data Warehouse 100

Knowledge Hut

OCTOBER 27, 2023

In this article, we will be discussing 4 types of d ata Science Projects for resume that can strengthen your skills and enhance your resume: Data Cleaning Exploratory Data Analysis Data Visualization Machine Learning Data Cleaning A   data scientist,   most likely spend nearly 80% of their time cleaning data.

Data Science 96

Data Science Coding Project Datasets 96

Cloudera

NOVEMBER 17, 2020

Once the prototype has been completely deployed, you will have an application that is able to make predictions to classify transactions as fraudulent or not: The data for this is the widely used credit card fraud dataset. Data analysis – create a plan to build the model.

Deep Learning 115

Deep Learning Machine Learning Raw Data Data Ingestion 115

Towards Data Science

MARCH 9, 2023

Code implementations for ML pipelines: from raw data to predictions Photo by Rodion Kutsaiev on Unsplash Real-life machine learning involves a series of tasks to prepare the data before the magic predictions take place. Those are the features and their respective data types: Image 1 —Features and data types.

Machine Learning 98

Machine Learning Building Datasets Big Data 98

Precisely

OCTOBER 5, 2023

According to the 2023 Data Integrity Trends and Insights Report , published in partnership between Precisely and Drexel University’s LeBow College of Business, 77% of data and analytics professionals say data-driven decision-making is the top goal of their data programs. That’s where data enrichment comes in.

Raw Data 69

Raw Data Insurance Datasets Telecommunication 69

Knowledge Hut

JULY 4, 2023

Data analysis and Interpretation: It helps in analyzing large and complex datasets by extracting meaningful patterns and structures. By identifying and understanding patterns within the data, valuable insights can be gained, leading to better decision-making, and understanding of underlying relationships.

Machine Learning 98

Machine Learning Medical Algorithm Deep Learning 98

Towards Data Science

AUGUST 31, 2023

Optimizing queries, improving runtimes, and geospatial data science applications Photo by Tamas Tuzes-Katai on Unsplash Intro: why is a spatial index useful? In doing geospatial data science work, it is very important to think about optimizing the code you are writing. This is where concepts such as spatial indices come in.

Data Engineering 98

Data Engineering Data Engineer Engineering Data Science 98

Data Engineering Podcast

JUNE 26, 2022

Summary The most complicated part of data engineering is the effort involved in making the raw data fit into the narrative of the business. Random data doesn’t do it — and production data is not safe (or legal) for developers to use. does exactly that. does exactly that.

Data Management 100

Data Management Management MongoDB MySQL 100

Confluent

SEPTEMBER 26, 2019

® , Go, and Python SDKs where an application can use SQL to query raw data coming from Kafka through an API (but that is a topic for another blog). Let’s now dig a little bit deeper into Kafka and Rockset for a concrete example of how to enable real-time interactive queries on large datasets, starting with Kafka.

Kafka 21

Kafka SQL BI Hadoop 21

LinkedIn Engineering

APRIL 4, 2023

raw data path, column mappings, aggregation function to be used, etc.) We introduced a data standardization step that mapped a raw metric dataset into a standardized dataset that our metric processing logic would understand. We did that by separating the metric’s configuration logic (i.e.

MySQL 122

MySQL Datasets Software Engineer Software Engineering 122

Cloudera

JANUARY 20, 2021

The value of the edge lies in acting at the edge where it has the greatest impact with zero latency before it sends the most valuable data to the cloud for further high-performance processing. Data Collection Using Cloudera Data Platform. STEP 1: Collecting the raw data.

Manufacturing 110

Manufacturing Data Warehouse Kafka Retail 110

Christophe Blefari

JANUARY 14, 2023

import polars as pl Then I can do my first CSV import, in the example I load a French railway open dataset about lost and found objects in stations. df = pl.read_csv("lost-objects-stations.csv", sep=";") Then you can use the same code as pandas to select the data (head, ["col"], etc.). seed round.

Python 130

Python Kafka Data Scala 130

Knowledge Hut

DECEMBER 22, 2023

Linear Algebra Linear Algebra is a mathematical subject that is very useful in data science and machine learning. A dataset is frequently represented as a matrix. Statistics Statistics are at the heart of complex machine learning algorithms in data science, identifying and converting data patterns into actionable evidence.

Hadoop 98

Hadoop Deep Learning Data Science Machine Learning 98

Netflix Tech

SEPTEMBER 10, 2019

Simulated dataset that shows what the distribution of play delay may look like. After recreating the dataset, you can plot the raw numbers and perform custom analyses to understand the distribution of the data across test cells. The library also provides helper methods which abstract accessing compressed or raw data.

Python 88

Python Raw Data SQL Datasets 88

U-Next

MARCH 7, 2023

Define Data Wrangling The process of data wrangling involves cleaning, structuring, and enriching raw data to make it more useful for decision-making. Data is discovered, structured, cleaned, enriched, validated, and analyzed. Values significantly out of a dataset’s mean are considered outliers.

Data Mining 96

Data Mining Scala Government Data Governance 96