AltexSoft

AUGUST 25, 2021

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. Plus, you likely won’t be able to use too much data. Assessing text data quality.

Process 139

Process Deep Learning Datasets Machine Learning 139

DataKitchen

SEPTEMBER 21, 2023

Running these automated tests as part of your DataOps and Data Observability strategy allows for early detection of discrepancies or errors. There are multiple locations where problems can happen in a data and analytic system. What is Data in Use?

Raw Data 67

Raw Data Data Business Intelligence Data Engineering 67

Wayne Yaddow

FEBRUARY 18, 2025

Selecting the strategies and tools for validating data transformations and data conversions in your data pipelines. Introduction Data transformations and data conversions are crucial to ensure that raw data is organized, processed, and ready for useful analysis.

Data Pipeline 52

Data Pipeline SQL Raw Data Python 52

Ascend.io

JULY 11, 2024

Metadata is the information that provides context and meaning to data, ensuring it’s easily discoverable, organized, and actionable. It enhances data quality, governance, and automation, transforming raw data into valuable insights. This is what managing data without metadata feels like. Chaos, right?

Metadata 52

Metadata IT Government High Quality Data 52

Snowflake

AUGUST 9, 2023

A solution that helps with supply chain issues, for instance, will need access to raw data on things such as weather, commodity risks, UPC-level attributes of products, and consumer transactions. That access needs to be fast and seamless.

Retail 52

Retail Electronics Raw Data Manufacturing 52

AltexSoft

AUGUST 3, 2021

Now, the primary function of data labeling is tagging objects on raw data to help the ML model make accurate predictions and estimations. That said, data annotation is key in training ML models if you want to achieve high-quality outputs. Guaranteeing high-quality data with consistency.

Datasets 59

Datasets High Quality Data Metadata Raw Data 59

Precisely

APRIL 24, 2023

At the opposite end of the spectrum, an abundance of data can be overwhelming. The key to effective data-driven decisions lies in curating enough high-quality data to adequately understand the situation, factor in the important variables, and draw confident conclusions. This process can be challenging.

Retail 52

Retail Raw Data High Quality Data Banking 52

Workfall

JULY 4, 2023

Reading Time: 8 minutes In the world of data engineering, a mighty tool called DBT (Data Build Tool) comes to the rescue of modern data workflows. Imagine a team of skilled data engineers on an exciting quest to transform raw data into a treasure trove of insights.

Data Warehouse 69

Data Warehouse SQL Database PostgreSQL 69

Monte Carlo

JULY 5, 2023

while overlooking or failing to understand what it really takes to make their tools — and, ultimately, their data initiatives — successful. When it comes to driving impact with your data, you first need to understand and manage that data’s quality.

High Quality Data 52

High Quality Data Data Software Engineer Software Engineering 52

Edureka

MARCH 15, 2025

This is due to the fact that they are not sufficiently refined and that they are trained using publicly available, publicly published raw data. Given where that training data came from, it’s probable that it might misrepresents or underrepresents particular groups or concepts be given the wrong label.

Entertainment 40

Entertainment Retail Education Healthcare 40

Databand.ai

JUNE 14, 2023

It enables: Enhanced decision-making: Accurate and reliable data allows businesses to make well-informed decisions, leading to increased revenue and improved operational efficiency. Risk mitigation: Data errors can result in expensive mistakes or even legal issues.

Amazon Web Services 40

Amazon Web Services Datasets High Quality Data ETL Tools 40

Knowledge Hut

JUNE 28, 2023

Data Sources Diverse and vast data sources, including structured, unstructured, and semi-structured data. Structured data from databases, data warehouses, and operational systems. Goal Extracting valuable information from raw data for predictive or descriptive purposes.

Data Mining 52

Data Mining Business Intelligence BI Structured Data 52

DareData

JULY 29, 2020

With these points in mind, I argue that the biggest hurdle to the widespread adoption of these advanced techniques in the healthcare industry is not intrinsic to the industry itself, or in any way related to its practitioners or patients, but simply the current lack of high-quality data pipelines.

Data Pipeline 52

Data Pipeline Healthcare Medical Pipeline-centric 52

Monte Carlo

DECEMBER 19, 2022

Too much data Too much data might not sound like a problem (it is called big data afterall), but when rows populate out of proportion, it can slow model performance and increase compute costs.

High Quality Data 52

High Quality Data Data SQL Bytes 52

Ascend.io

JANUARY 10, 2024

AI models are only as good as the data they consume, making continuous data readiness crucial. Here are the key processes that need to be in place to guarantee consistently high-quality data for AI models: Data Availability: Establish a process to regularly check on data availability.

Data Pipeline 52

Data Pipeline Government Data Governance Raw Data 52

Knowledge Hut

JANUARY 24, 2024

They employ a wide array of tools and techniques, including statistical methods and machine learning, coupled with their unique human understanding, to navigate the complex world of data. A significant part of their role revolves around collecting, cleaning, and manipulating data, as raw data is seldom pristine.

Database-centric 52

Database-centric Data Science Machine Learning Algorithm 52

DataKitchen

JULY 27, 2023

Azure Databricks Delta Live Table s: These provide a more straightforward way to build and manage Data Pipelines for the latest, high-quality data in Delta Lake. Azure Blob Storage serves as the data lake to store raw data. Databricks Notebooks are often used in conjunction with Workflows.

Data Pipeline 52

Data Pipeline BI Machine Learning Data Preparation 52

Monte Carlo

APRIL 24, 2023

Data ingestion When we think about the flow of data in a pipeline, data ingestion is where the data first enters our platform. There are two primary types of raw data.

Data Pipeline 52

Data Pipeline Building Data Ingestion BI 52

Databand.ai

JULY 10, 2023

Observability platforms not only supply raw data but also offer actionable insights through visualizations, dashboards, and alerts. Databand allows data engineering and data science teams to define data quality rules, monitor data consistency, and identify data drift or anomalies.

Data Pipeline 52

Data Pipeline Algorithm Data Engineering Data Engineer 52

Monte Carlo

JUNE 23, 2022

Whether the end result is a weekly report, dashboard, or embedded in a customer facing application, data products require a level of polish and data curation that is antithetical to unorganized sprawl. Your ability to pipe data is virtually limitless, but you are constrained by the capacity of humans to make it sustainably meaningful.

Big Data 40

Big Data Management Machine Learning Data Warehouse 40

Monte Carlo

MAY 23, 2023

Business data assets at Assurance are loaded into the company’s lakehouse architecture through various methods, then stored in several data stores. The data team then uses tools like dbt and Airflow to refine, model and transform raw data into usable, query-able assets through Trino and Starburst.

Insurance 52

Insurance Business Intelligence Machine Learning Data 52

Monte Carlo

AUGUST 31, 2023

Not long after data warehouses moved to the cloud, so too did data lakes (a place to transform and store unstructured data), giving data teams even greater flexibility when it comes to managing their data assets. That is the question – at least if you ask a data engineer.

Data Lake 52

Data Lake Data Pipeline Unstructured Data Data Warehouse 52

Knowledge Hut

JANUARY 25, 2024

Trustworthy Analytics: Reliable data supports accurate statistical analysis. Enhanced Visualization: Clean data leads to clearer data visualizations. Efficient Machine Learning: High-quality data is vital for training accurate ML models. What is the difference between data cleaning and data transformation?

Data Cleanse 52

Data Cleanse Datasets Data Preparation Data Science 52

Monte Carlo

AUGUST 30, 2023

The `dbt run` command will compile and execute your models, thus transforming your raw data into analysis-ready tables. Once the models are created and data transformed, `dbt test` should be executed. This command runs all tests defined in your dbt project against the transformed data.

SQL 52

SQL Datasets Database High Quality Data 52

Monte Carlo

JANUARY 6, 2023

While tempting to write-off our product stakeholders as not understanding our field, it’s very often because analysts are stuck responding to rudimentary questions that could be addressed with better access to high-quality data, rather than spending time on more sophisticated, thorough, or profound analysis that clearly demonstrates their expertise.

Building 52

Building Project BI Data 52

DataKitchen

OCTOBER 2, 2023

Providing a comprehensive suite of features, from alerts and analytics to fast integration and data tests, ‘The Traveler’ empowers the End-to-End Data Product Team to manage their data landscape proactively. The Hub Data Journey provides the raw data and adds value through a ‘contract.

Data Ingestion 40

Data Ingestion Data Government Datasets 40

Striim

JANUARY 8, 2025

A 2023 Salesforce study revealed that 80% of business leaders consider data essential for decision-making. However, a Seagate report found that 68% of available enterprise data goes unleveraged, signaling significant untapped potential for operational analytics to transform raw data into actionable insights.

BI 52

BI Business Analyst Retail Raw Data 52