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

DataKitchen

MAY 10, 2024

The Third of Five Use Cases in Data Observability Data Evaluation: This involves evaluating and cleansing new datasets before being added to production. This process is critical as it ensures data quality from the onset. Examples include regular loading of CRM data and anomaly detection.

Raw Data 50

Raw Data Data Ingestion Datasets Data 50

Ascend.io

AUGUST 15, 2023

While terms like “Fivetran ETL” or “Fivetran data pipeline” are echoing in the corridors of data professionals, the truth is, Fivetran is primarily an expert on data ingestion — just the first step in a much broader and nuanced data management process.

Data Management 52

Data Management Management Data Ingestion Data Pipeline 52

Towards Data Science

NOVEMBER 16, 2023

Data Management A tutorial on how to use VDK to perform batch data processing Photo by Mika Baumeister on Unsplash Versatile Data Ki t (VDK) is an open-source data ingestion and processing framework designed to simplify data management complexities. link] Summary Congratulations!

Data Process 74

Data Process Process Raw Data Data 74

Ascend.io

FEBRUARY 6, 2023

Data Flow – is an individual data pipeline. Data Flows include the ingestion of raw data, transformation via SQL and python, and sharing of finished data products. Data Plane – is the data cloud where the data pipeline workload runs, like Databricks, BigQuery, and Snowflake.

Cloud 52

Cloud Data Ingestion Raw Data Data Pipeline 52

Ascend.io

FEBRUARY 6, 2023

Data Flow – is an individual data pipeline. Data Flows include the ingestion of raw data, transformation via SQL and python, and sharing of finished data products. Data Plane – is the data cloud where the data pipeline workload runs, like Databricks, BigQuery, and Snowflake.

Cloud 52

Cloud Data Ingestion Raw Data Data Pipeline 52

Databand.ai

AUGUST 30, 2023

DataOps is a collaborative approach to data management that combines the agility of DevOps with the power of data analytics. It aims to streamline data ingestion, processing, and analytics by automating and integrating various data workflows.

Architecture 52

Architecture Data Ingestion Data Governance Data Cleanse 52

Monte Carlo

APRIL 24, 2023

In this article, we’ll dive deep into the data presentation layers of the data stack to consider how scale impacts our build versus buy decisions, and how we can thoughtfully apply our five considerations at various points in our platform’s maturity to find the right mix of components for our organizations unique business needs.

Data Pipeline 52

Data Pipeline Building Data Ingestion BI 52

Cloudera

JANUARY 20, 2021

The data journey is not linear, but it is an infinite loop data lifecycle – initiating at the edge, weaving through a data platform, and resulting in business imperative insights applied to real business-critical problems that result in new data-led initiatives. Data Collection Using Cloudera Data Platform.

Manufacturing 109

Manufacturing Data Warehouse Kafka Retail 109

Snowflake

JUNE 6, 2024

Schedule data ingestion, processing, model training and insight generation to enhance efficiency and consistency in your data processes. Access Snowflake platform capabilities and data sets directly within your notebooks.

SQL 95

SQL Python Machine Learning Data Workflow 95

Knowledge Hut

DECEMBER 7, 2023

Welcome to the comprehensive guide for beginners on harnessing the power of Microsoft's remarkable data visualization tool - Power BI. In today's data-driven world, the ability to transform raw data into meaningful insights is paramount, and Power BI empowers users to achieve just that. What is Power BI?

BI 52

BI Raw Data Datasets Business Intelligence 52

Ascend.io

JANUARY 2, 2024

The key differentiation lies in the transformational steps that a data pipeline includes to make data business-ready. Ultimately, the core function of a pipeline is to take raw data and turn it into valuable, accessible insights that drive business growth. cleaning, formatting)?

Data Pipeline 52

Data Pipeline Building Raw Data Data Warehouse 52

AltexSoft

AUGUST 29, 2023

The term was coined by James Dixon , Back-End Java, Data, and Business Intelligence Engineer, and it started a new era in how organizations could store, manage, and analyze their data. This article explains what a data lake is, its architecture, and diverse use cases. Video explaining how data streaming works.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

Cloudyard

MARCH 4, 2023

DCDW Architecture Above all, Architecture was divided into three Business layers: Firstly,Agile Data ingestion : Heterogeneous Source System fed the data into Cloud. Respective Cloud would consume/Store the data in bucket or containers. Load the data AS-IS into Snowflake called RAW layer.

Architecture 52

Architecture Cloud Metadata Data Ingestion 52

Ascend.io

AUGUST 29, 2023

Similarly , in data, every step of the pipeline, from data ingestion to delivery, plays a pivotal role in delivering impactful results. In this article, we’ll break down the intricacies of an end-to-end data pipeline and highlight its importance in today’s landscape.

Data Pipeline 52

Data Pipeline Pipeline-centric Database-centric Data Ingestion 52

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. report having current investments in automation, 85% of data teams plan on investing in automation in the next 12 months. In fact, while only 3.5% That’s where our friends at Ascend.io

Data Management 100

Data Management Management MongoDB Scala 100

Ascend.io

FEBRUARY 23, 2024

For this reason, your data platform becomes the foundation for your AI initiatives. Robust Data Ingestion AI systems thrive on diverse data sources. Your platform should be equipped with robust mechanisms for data ingestion and integration, enabling seamless flow of data from various sources into the system.

Cloud Storage 52

Cloud Storage Data Ingestion Machine Learning Algorithm 52

DareData

JULY 5, 2023

If you work at a relatively large company, you've seen this cycle happening many times: Analytics team wants to use unstructured data on their models or analysis. For example, an industrial analytics team wants to use the logs from raw data. The Data Warehouse(s) facilitates data ingestion and enables easy access for end-users.

Data Lake 52

Data Lake Building Raw Data ETL Tools 52

Snowflake

MARCH 13, 2023

Architecture designed to empower more clients Gem’s cybersecurity platform starts with raw data ingestion from its clients’ cloud environments. Gem uses the fully-managed Snowpipe service, allowing it to stream and process source data in near-real time. Pushing and scaling are super smooth.

Cloud 52

Cloud Building Data Ingestion AWS 52

Striim

AUGUST 7, 2024

Transform Raw Data into AI-generated Actions and Insights in Seconds In today’s fast-paced business environment, the ability to quickly transform raw data into actionable insights is crucial. POS transactions training data span 79 days starting from (2024-02-01 to 2024-04-20).

IT 52

IT Entertainment MySQL Raw Data 52

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. Feature engineering: Data is transformed to support ML model training. ML workflow, ubr.to/3EJHjvm

Engineering 84

Engineering Raw Data Data Science Machine Learning 84

Cloudera

NOVEMBER 17, 2020

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. . The process followed in this prototype covers several steps that you should follow: Data Ingest – move the raw data to a more suitable storage location.

Deep Learning 115

Deep Learning Machine Learning Raw Data Data Ingestion 115

The Modern Data Company

MAY 8, 2023

The Data Lake: A Reservoir of Unstructured Potential A data lake is a centralized repository that stores vast amounts of raw data. It can store any type of data — structured, unstructured, and semi-structured — in its native format, providing a highly scalable and adaptable solution for diverse data needs.

Data Management 52

Data Management Management Data Lake Data Governance 52

The Modern Data Company

MAY 8, 2023

The Data Lake: A Reservoir of Unstructured Potential A data lake is a centralized repository that stores vast amounts of raw data. It can store any type of data — structured, unstructured, and semi-structured — in its native format, providing a highly scalable and adaptable solution for diverse data needs.

Data Management 52

Data Management Data Lake Management Data Governance 52

The Modern Data Company

MAY 8, 2023

The Data Lake: A Reservoir of Unstructured Potential A data lake is a centralized repository that stores vast amounts of raw data. It can store any type of data — structured, unstructured, and semi-structured — in its native format, providing a highly scalable and adaptable solution for diverse data needs.

Data Management 52

Data Management Management Data Lake Data Governance 52

DataKitchen

SEPTEMBER 21, 2023

In the contemporary data landscape, data teams commonly utilize data warehouses or lakes to arrange their data into L1, L2, and L3 layers. The current landscape of Data Observability Tools shows a marked focus on “Data in Place,” leaving a significant gap in the “Data in Use.”

Raw Data 69

Raw Data Data Business Intelligence Data Engineer 69

Cloudera

MAY 19, 2021

Data Ingestion. The raw data is in a series of CSV files. We will firstly convert this to parquet format as most data lakes exist as object stores full of parquet files. Common problems at this stage can be related to GPU versions. RAPIDS is only supported on Pascal or newer NVIDIA GPUs.

Machine Learning 137

Machine Learning Datasets Data Science Raw Data 137

DataKitchen

OCTOBER 2, 2023

Data Teams and Their Types of Data Journeys In the rapidly evolving landscape of data management and analytics, data teams face various challenges ranging from data ingestion to end-to-end observability. It explores why DataKitchen’s ‘Data Journeys’ capability can solve these challenges.

Data Ingestion 40

Data Ingestion Data Government Datasets 40

Knowledge Hut

NOVEMBER 2, 2023

Azure Data Engineer vs Azure Devops: Roles and Responsibilities Azure Data Engineers are responsible for designing, implementing, and managing data solutions on Microsoft's Azure cloud platform. They work on creating efficient data pipelines, optimizing data processing, and ensuring data availability for reporting and analysis.

Data Engineer 52

Data Engineer Data Engineering Engineering Pipeline-centric 52

AltexSoft

JUNE 26, 2023

Data collection vs data integration vs data ingestion Data collection is often confused with data ingestion and data integration — other important processes within the data management strategy. While all three are about data acquisition, they have distinct differences.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

The Modern Data Company

JULY 29, 2024

Already operating at capacity, data teams often find themselves repeating efforts, rebuilding similar data pipelines and models for each new project. The consequences of these challenges are stark: the journey from raw data to actionable insights has become excruciatingly long.

Data Architecture 52

Data Architecture Architecture Building Pipeline-centric 52

Knowledge Hut

JANUARY 18, 2024

Let us now look into the differences between AI and Data Science: Data Science vs Artificial Intelligence [Comparison Table] SI Parameters Data Science Artificial Intelligence 1 Basics Involves processes such as data ingestion, analysis, visualization, and communication of insights derived.

Data Science 98

Data Science Deep Learning Business Analyst Data Mining 98

Cloudera

NOVEMBER 19, 2020

The modeling process begins with data collection. Here, Cloudera Data Flow is leveraged to build a streaming pipeline which enables the collection, movement, curation, and augmentation of raw data feeds. These feeds are then enriched using external data sources (e.g.,

Government 119

Government Machine Learning Algorithm Raw Data 119

Towards Data Science

MAY 3, 2023

One such tool is the Versatile Data Kit (VDK), which offers a comprehensive solution for controlling your data versioning needs. VDK helps you easily perform complex operations, such as data ingestion and processing from different sources, using SQL or Python.

Data Lake 82

Data Lake SQL Data Data Warehouse 82

Monte Carlo

NOVEMBER 14, 2023

Data incompleteness: Corrupted, incomplete, or data missing from your tables, such as data ingested without all the required fields or data damaged due to human or technical errors.

Data Lake 64

Data Lake Metadata Data Warehouse SQL 64

WeCloudData

OCTOBER 19, 2021

Resolution In order to meet the business requirements for a job market analysis platform & dashboard, WeCloudData helped the client leverage a suite of cloud platforms & tools to enable a data pipeline in multiple stages: Ingest job data from multiple sources and store the raw data in a cloud data lake Process the raw data with Python & (..)

Consulting 52

Consulting Raw Data Data Lake Data Pipeline 52

WeCloudData

OCTOBER 19, 2021

Resolution In order to meet the business requirements for a job market analysis platform & dashboard, WeCloudData helped the client leverage a suite of cloud platforms & tools to enable a data pipeline in multiple stages: Ingest job data from multiple sources and store the raw data in a cloud data lake Process the raw data with Python & (..)

Consulting 52

Consulting Raw Data Data Lake Data Pipeline 52