AltexSoft

AUGUST 25, 2021

And this technology of Natural Language Processing is available to all businesses. Available methods for text processing and which one to choose. Specifics of data used in NLP. What is Natural Language Processing? Here are some big text processing types and how they can be applied in real life. Main NLP use cases.

Process 139

Process Deep Learning Datasets Machine Learning 139

Cloudyard

JANUARY 15, 2025

Read Time: 2 Minute, 33 Second Snowflakes PARSE_DOCUMENT function revolutionizes how unstructured data, such as PDF files, is processed within the Snowflake ecosystem. However, Ive taken this a step further, leveraging Snowpark to extend its capabilities and build a complete data extraction process. Why Use PARSE_DOC?

Data Cleanse 52

Data Cleanse Insurance Raw Data Unstructured Data 52

The Pragmatic Engineer

OCTOBER 17, 2024

Code and raw data repository:   Version control: GitHub Heavily using GitHub Actions for things like getting warehouse data from vendor APIs, starting cloud servers, running benchmarks, processing results, and cleaning up after tuns. Internal comms: Chat: Slack Coordination / project management: Linear 3.

Cloud 326

Cloud AWS Metadata Cloud Computing 326

Christophe Blefari

MARCH 1, 2023

In the ELT, the load is done before the transform part without any alteration of the data leaving the raw data ready to be transformed in the data warehouse. In a simple words dbt sits on top of your raw data to organise all your SQL queries that are defining your data assets.

Data Warehouse 278

Data Warehouse SQL Metadata Raw Data 278

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

Analytics Vidhya

FEBRUARY 25, 2023

The need for a data lake arises from the growing volume, variety, and velocity of data companies need to manage and analyze.

Cloud Storage 162

Cloud Storage Data Lake Cloud Unstructured Data 162

Ascend.io

OCTOBER 28, 2024

What is Data Transformation? Data transformation is the process of converting raw data into a usable format to generate insights. It involves cleaning, normalizing, validating, and enriching data, ensuring that it is consistent and ready for analysis.

Raw Data 52

Raw Data Datasets Aggregated Data Data Pipeline 52

Snowflake

NOVEMBER 11, 2024

Here’s how Snowflake Cortex AI and Snowflake ML are accelerating the delivery of trusted AI solutions for the most critical generative AI applications: Natural language processing (NLP) for data pipelines: Large language models (LLMs) have a transformative potential, but they often batch inference integration into pipelines, which can be cumbersome.

Unstructured Data 97

Unstructured Data SQL AWS Healthcare 97

Hevo

DECEMBER 6, 2024

Data preparation tools are very important in the analytics process. They transform raw data into a clean and structured format ready for analysis. These tools simplify complex data-wrangling tasks like cleaning, merging, and formatting, thus saving precious time for analysts and data teams. 

Data Preparation 52

Data Preparation Raw Data Data Process 52

Cloudyard

MAY 4, 2025

This combination streamlines ETL processes, increases flexibility, and reduces manual coding. In this blog, I walk you through a use case where DBT orchestrates an automated S3-to-Snowflake ingestion flow using Snowflake capabilities like file handling, schema inference, and data loading. But Isnt DBT Just for Transformations?

ETL Tools 59

ETL Tools Raw Data SQL Python 59

Cloudera

JANUARY 9, 2025

AI today involves ML, advanced analytics, computer vision, natural language processing, autonomous agents, and more. It means combining data engineering, model ops, governance, and collaboration in a single, streamlined environment. Beyond Buzzwords: Real Results We know AI can sound like hype.

Machine Learning 85

Machine Learning Raw Data Government Algorithm 85

DataKitchen

DECEMBER 6, 2024

Would you like help maintaining high-quality data across every layer of your Medallion Architecture? Like an Olympic athlete training for the gold, your data needs a continuous, iterative process to maintain peak performance.

Architecture 52

Architecture Raw Data High Quality Data Data Validation 52

Edureka

MAY 27, 2025

The architecture of Microsoft Fabric is based on several essential elements that work together to simplify data processes: 1. OneLake Data Lake OneLake provides a centralized data repository and is the fundamental storage layer of Microsoft Fabric. Transform Your Data Analytics with Microsoft Fabric!

Architecture 52

Architecture BI Business Intelligence Raw Data 52

Engineering at Meta

JANUARY 21, 2025

Strobelight is also not a single profiler but an orchestrator of many different profilers (even ad-hoc ones) that runs on all production hosts at Meta, collecting detailed information about CPU usage, memory allocations, and other performance metrics from running processes.

Technology 118

Technology Metadata Utilities Engineering 118

Monte Carlo

NOVEMBER 21, 2024

That’s where data pipeline design patterns come in. They’re basically architectural blueprints for moving and processing your data. So, why does choosing the right data pipeline design matter? In this guide, we’ll explore the patterns that can help you design data pipelines that actually work.

Data Pipeline 52

Data Pipeline Designing Lambda Architecture Kafka 52

Edureka

MAY 8, 2025

Real-World Data Engineering Applications Data engineering is an important area in today’s data world because it studies how to build, manage, and organize systems that collect, store, and process large amounts of data. Here are the 9 prominent data engineering applications: 1.

Data Engineering 52

Data Engineering Data Engineer Engineering Telecommunication 52

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. The post Use Data Enrichment to Supercharge AI appeared first on Precisely.

Raw Data 120

Raw Data Insurance Data Portfolio 120

Towards Data Science

FEBRUARY 9, 2023

An experiment on BigQuery If you are processing a couple of MB or GB with your dbt model, this is not a post for you; you are doing just fine! This post is for those poor souls that need to scan terabytes of data in BigQuery to calculate some counts, sums, or rolling totals over huge event data on a daily or even at a higher frequency basis.

Big Data 98

Big Data Raw Data Aggregated Data Data 98

Towards Data Science

FEBRUARY 6, 2024

ERP and CRM systems are designed and built to fulfil a broad range of business processes and functions. This generalisation makes their data models complex and cryptic and require domain expertise. Searching for data Imagine being a data engineer/analyst tasked with identifying the top-selling products within your company.

Systems 98

Systems Raw Data Metadata Data Cleanse 98

Maxime Beauchemin

AUGUST 28, 2017

In modern large organizations, where hundred of people are involved in the data generation side of the analytical process, consensus seeking is challenging, when not outright impossible in a timely fashion. In my experience, it’s rare to find any sort of decent dev or test environments in the big data world.

Data Engineering 174

Data Engineering Data Engineer Engineering Software Engineering 174

DataKitchen

AUGUST 9, 2021

The data industry has a wide variety of approaches and philosophies for managing data: Inman data factory, Kimball methodology, s tar schema , or the data vault pattern, which can be a great way to store and organize raw data, and more. Data mesh does not replace or require any of these.

Pharmaceutical 98

Pharmaceutical Raw Data Data Data Lake 98

Knowledge Hut

APRIL 19, 2023

The process of gathering and compiling data from various sources is known as data Aggregation. Businesses and groups gather enormous amounts of data from a variety of sources, including social media, customer databases, transactional systems, and many more. What is Data Aggregation?

Process 59

Process Data Mining Aggregated Data Portfolio 59

Snowflake

JUNE 20, 2024

In the age of AI, enterprises are increasingly looking to extract value from their data at scale but often find it difficult to establish a scalable data engineering foundation that can process the large amounts of data required to build or improve models. Snowflake customers see an average of 4.6x

Data Engineering 110

Data Engineering Data Engineer Scala Engineering 110

Snowflake

MARCH 30, 2023

Collecting, cleaning, and organizing data into a coherent form for business users to consume are all standard data modeling and data engineering tasks for loading a data warehouse. Based on Tecton blog So is this similar to data engineering pipelines into a data lake/warehouse?

Engineering 104

Engineering Raw Data Data Science Machine Learning 104

Edureka

APRIL 14, 2025

The other is a more comprehensive environment that supports data integration, engineering, warehousing, and real-time analytics — all in one unified experience. The Real-World Example: Retail Giant’s Data Journey will be examined next.

BI 40

BI Business Intelligence Raw Data Retail 40

Edureka

MAY 27, 2025

Salesforce created Tableau, a popular tool for business intelligence and data visualization. It lets users create interactive, shareable dashboards and reports from raw data. What is Tableau? What distinguishes Microsoft Fabric from Salesforce? Which is superior, Tableau or SAP? Decide if you require focused analytics or ERP.

BI 40

BI Data Lake Business Intelligence Raw Data 40

Cloudera

MAY 19, 2021

This year, we expanded our partnership with NVIDIA , enabling your data teams to dramatically speed up compute processes for data engineering and data science workloads with no code changes using RAPIDS AI. The script will go through loading RAPIDs libraries then leveraging them to load and processing a datafile.

Machine Learning 137

Machine Learning Data Science Datasets Raw Data 137

ThoughtSpot

APRIL 22, 2025

This requires multiple layers of computational intelligence to transform raw data into meaningful business insights which no other tool on the market can do. When asked a why question, Spotter follows the same logical process that your favorite analyst would follow.

BI 59

BI Datasets Business Intelligence Raw Data 59

Cloudera

JANUARY 20, 2021

The six steps are: Data Collection – data ingestion and monitoring at the edge (whether the edge be industrial sensors or people in a brick and mortar retail store). Data Enrichment – data pipeline processing, aggregation & management to ready the data for further refinement.

Manufacturing 110

Manufacturing Data Warehouse Kafka Retail 110

Monte Carlo

JANUARY 29, 2025

The company uses a medallion architecture, where data flows from raw (bronze) to standardized (silver) to aggregated (gold) layers. But in practice, each team creates their own separate data transformations directly from the raw data. This practice isnt unusual, but it can lead to problems.

Media 52

Media Data Science Datasets Raw Data 52

Striim

NOVEMBER 17, 2023

Real-time data processing in the world of machine learning allows data scientists and engineers to focus on model development and monitoring. Striim’s strength lies in its capacity to connect to over 150 data sources, enabling real-time data acquisition from virtually any location and simplifying data transformations.

Machine Learning 52

Machine Learning Data Process PostgreSQL Process 52

ThoughtSpot

SEPTEMBER 6, 2023

Those coveted insights live at the end of a process lovingly known as the data pipeline. The pathway from ETL to actionable analytics can often feel disconnected and cumbersome, leading to frustration for data teams and long wait times for business users. Keep reading to see how it works.

Data Workflow 106

Data Workflow Raw Data Data Lake Business Intelligence 106

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

Edureka

MARCH 15, 2025

Within the larger field of artificial intelligence, Small Language Models (SLMs) are a specialized subset designed for Natural Language Processing (NLP). They are distinguished by their small size and low processing power. Although QAT can generate a more accurate model, PTQ doesn’t need as much processing power or training data.

Entertainment 74

Entertainment Retail Education Datasets 74

Cloudera

NOVEMBER 17, 2020

Once you have deployed the template and all the CML artifacts that go with it, you can unpick and work it backward to map the process to your own data in your own environment. . The data and the techniques presented in this prototype are still applicable as creating a PCA feature store is often part of the machine learning process. .

Deep Learning 115

Deep Learning Machine Learning Raw Data Data Ingestion 115

RandomTrees

MARCH 10, 2025

Let’s explore predictive analytics, the ground-breaking technology that enables companies to anticipate patterns, optimize processes, and reach well-informed conclusions. From Information to Insight The difficulty is not gathering data but making sense of it. Want to know more? Let’s examine its relevance and operation.

Retail 52

Retail Data Governance Hospitality Banking 52

DataKitchen

AUGUST 19, 2021

Two data sets of physicians may not match. They each tell a different story about the data. Figure 3 shows an example processing architecture with data flowing in from internal and external sources. Each data source is updated on its own schedule, for example, daily, weekly or monthly.

Pharmaceutical 98

Pharmaceutical Data Lake Data Warehouse Raw Data 98