phData

OCTOBER 25, 2024

“Quality over Quantity” is a phrase we hear regularly in life, but when it comes to the world of data, we often fail to adhere to this rule. Data Quality Monitoring implements quality checks in operational data processes to ensure that the data meets pre-defined standards and business rules.

Data Quality 52

Data Quality Data Pipeline Data Governance Database 52

Smart Data Collective

APRIL 29, 2020

The extraction of raw data, transforming to a suitable format for business needs, and loading into a data warehouse. Data transformation. This process helps to transform raw data into clean data that can be analysed and aggregated. Data analytics and visualisation. Microsoft Azure.

Data Warehouse 98

Data Warehouse Azure SQL ETL 98

Pickl AI

OCTOBER 17, 2024

Introduction ETL plays a crucial role in Data Management. This process enables organisations to gather data from various sources, transform it into a usable format, and load it into data warehouses or databases for analysis. Loading The transformed data is loaded into the target destination, such as a data warehouse.

ETL 52

ETL Data Warehouse Data Quality Data Governance 52

Pickl AI

MARCH 19, 2025

It is widely used for storing and managing structured data, making it an essential tool for data engineers. MongoDB MongoDB is a NoSQL database that stores data in flexible, JSON-like documents. Apache Spark Apache Spark is a powerful data processing framework that efficiently handles Big Data.

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52

Alation

AUGUST 4, 2022

“File-based storage of data is the norm even under more relational models. [In In the cloud], Graph databases, document stores, file stores, relational stores all now exist, each addressing different challenges.” In this way, the cloud has democratized access to some of the best outputs of big data.

Big Data 95

Big Data Big Data Apache Kafka Data Lakes 95

ODSC - Open Data Science

FEBRUARY 24, 2023

Data Quality Now that you’ve learned more about your data and cleaned it up, it’s time to ensure the quality of your data is up to par. With these data exploration tools, you can determine if your data is accurate, consistent, and reliable.

Exploratory Data Analysis 126

Exploratory Data Analysis Data Visualization Data Analysis Data Analysis 126

Alation

JULY 19, 2022

For example, a new data scientist who is curious about which customers are most likely to be repeat buyers, might search for customer data only to discover an article documenting a previous project that answered their exact question. Modern data catalogs also facilitate data quality checks.

Data Scientist 59

Data Scientist Data Quality Data Science Data Analyst 59

phData

DECEMBER 4, 2024

Implementing Generative AI can be difficult as there are some hurdles to overcome for any business to get up and running: Data Quality You get the same quality output as the data you use for any AI system, so having accurate and unbiased data is of the utmost importance.

AI 52

AI AI Data Warehouse Data Quality 52

phData

SEPTEMBER 19, 2023

By incorporating metadata into the data model, users can easily discover, understand, and interpret the data stored in the lake. With the amounts of data involved, this can be crucial to utilizing a data lake effectively. Inaccurate or inconsistent data can undermine decision-making and erode trust in analytics.

Data Lakes 52

Data Lakes Data Modeling Data Models Data Warehouse 52

Pickl AI

APRIL 9, 2025

By 2025, global data volumes are expected to reach 181 zettabytes, according to IDC. To harness this data effectively, businesses rely on ETL (Extract, Transform, Load) tools to extract, transform, and load data into centralized systems like data warehouses.

ETL 52

ETL Data Warehouse AWS Business Intelligence 52

Pickl AI

AUGUST 11, 2024

Additionally, it addresses common challenges and offers practical solutions to ensure that fact tables are structured for optimal data quality and analytical performance. Introduction In today’s data-driven landscape, organisations are increasingly reliant on Data Analytics to inform decision-making and drive business strategies.

Data Quality 52

Data Quality Data Warehouse Data Governance Analytics 52

AWS Machine Learning Blog

SEPTEMBER 18, 2024

Additionally, Feast promotes feature reuse, so the time spent on data preparation is reduced greatly. It promotes a disciplined approach to data modeling, making it easier to ensure data quality and consistency across the ML pipelines.

AWS 128

AWS Machine Learning Machine Learning ML 128

IBM Journey to AI blog

JULY 3, 2024

As data types and applications evolve, you might need specialized NoSQL databases to handle diverse data structures and specific application requirements. The consequences of using poor-quality data are far-reaching, including erosion of customer trust, regulatory noncompliance and financial and reputational damage.

AI 45

AI AI Data Quality Database 45

Alation

DECEMBER 21, 2022

Master Data Management (MDM) and data catalog growth are accelerating because organizations must integrate more systems, comply with privacy regulations, and address data quality concerns. What Is Master Data Management (MDM)? Data Catalog and Master Data Management. Assess Data Quality.

Data Quality 52

Data Quality Data Warehouse Data Profiling Data Governance 52

IBM Journey to AI blog

JULY 27, 2023

Precisely conducted a study that found that within enterprises, data scientists spend 80% of their time cleaning, integrating and preparing data , dealing with many formats, including documents, images, and videos. Overall placing emphasis on establishing a trusted and integrated data platform for AI.

AI 69

AI AI Data Scientist Data Quality 69

phData

OCTOBER 12, 2022

Hosted Doc Site for Documentation One of the most powerful features of dbt can be the documentation you generate. This documentation can give different users insight into where data came from, what the profile of the data is, what the SQL looked like, and the DAG to know where the data is being used.

SQL 52

SQL Data Warehouse Data Visualization Cloud Data 52

Pickl AI

AUGUST 9, 2024

Document Hierarchy Structures Maintain thorough documentation of hierarchy designs, including definitions, relationships, and data sources. This documentation is invaluable for future reference and modifications. Data Quality Issues Inconsistent or incomplete data can hinder the effectiveness of hierarchies.

Data Warehouse 52

Data Warehouse Data Quality ETL Business Intelligence 52

Alation

JUNE 30, 2022

We are now seeing a similar transformation in the world of data, where there’s tension between the old world (single-source-of-truth data warehouses with top-down data governance) and the new world (distributed, self-service analytics with grassroots management). Data quality can change with time.

Data Warehouse 52

Data Warehouse Data Quality Machine Learning Machine Learning 52

phData

AUGUST 10, 2023

Data Vault - Data Lifecycle Architecturally, let’s understand the data lifecycle in the data vault into the following layers, which play a key role in choosing the right pattern and tools to implement. Data Acquisition: Extracting data from source systems and making it accessible.

SQL 52

SQL Data Observability Data Quality Data Pipeline 52

Flipboard

MAY 9, 2025

Additional considerations Though the potential of this approach is significant, there are several challenges to consider: Data quality High-quality, diverse input data is key to effective model performance.

AWS 100

AWS Natural Language Processing AI AI 100

phData

JULY 18, 2023

With the birth of cloud data warehouses, data applications, and generative AI , processing large volumes of data faster and cheaper is more approachable and desired than ever. First up, let’s dive into the foundation of every Modern Data Stack, a cloud-based data warehouse.

Data Warehouse 52

Data Warehouse Analytics Analytics Cloud Data 52

Pickl AI

JUNE 7, 2024

Top contenders like Apache Airflow and AWS Glue offer unique features, empowering businesses with efficient workflows, high data quality, and informed decision-making capabilities. Introduction In today’s business landscape, data integration is vital. Also Read: Top 10 Data Science tools for 2024. What is ETL?

ETL 40

ETL Data Quality Data Pipeline Data Warehouse 40

Alation

SEPTEMBER 7, 2021

In the next section, let’s take a deeper look into how these key attributes help data scientists and analysts make faster, more informed decisions, while supporting stewards in their quest to scale governance policies on the Data Cloud easily. Find Trusted Data. Verifying quality is time consuming. Two problems arise.

Data Governance 59

Data Governance Data Scientist Data Quality Data Profiling 59

Alation

FEBRUARY 7, 2023

It wouldn’t be until 2013 that the topic of data lineage would surface again – this time while working on a data warehouse project. Data warehouses obfuscate data’s origin In 2013, I was a Business Intelligence Engineer at a financial services company. What’s the right lineage level? It depends!

Data Warehouse 52

Data Warehouse ETL Business Intelligence Business Intelligence 52

IBM Journey to AI blog

OCTOBER 12, 2023

To optimize data analytics and AI workloads, organizations need a data store built on an open data lakehouse architecture. This type of architecture combines the performance and usability of a data warehouse with the flexibility and scalability of a data lake.

AI 93

AI AI Data Scientist Data Governance 93

phData

OCTOBER 17, 2024

dbt offers a SQL-first transformation workflow that lets teams build data transformation pipelines while following software engineering best practices like CI/CD, modularity, and documentation. The Data Source Tool can automate scanning DDL and profiling tables between source and target, comparing them, and then reporting findings.

AI 52

AI AI SQL Data Quality 52

phData

JANUARY 24, 2024

Fivetran includes features like data movement, transformations, robust security, and compatibility with third-party tools like DBT, Airflow, Atlan, and more. Its seamless integration with popular cloud data warehouses like Snowflake can provide the scalability needed as your business grows.

Data Warehouse 52

Data Warehouse Data Pipeline Data Governance Cloud Data 52

Alation

OCTOBER 18, 2022

Alation is pleased to be named a dbt Metrics Partner and to announce the start of a partnership with dbt, which will bring dbt data into the Alation data catalog. In the modern data stack, dbt is a key tool to make data ready for analysis. Purchase date represents one customer touch point.

Data Analyst 52

Data Analyst Data Engineering Data Engineering Data Engineer 52

Snorkel AI

JANUARY 24, 2023

Data science and machine learning teams use Snorkel Flow’s programmatic labeling to intelligently capture knowledge from various sources such as previously labeled data (even when imperfect), heuristics from subject matter experts, business logic, and even the latest foundation models, then scale this knowledge to label large quantities of data.

AI 52

AI AI ML ML 52

Snorkel AI

JANUARY 24, 2023

Data science and machine learning teams use Snorkel Flow’s programmatic labeling to intelligently capture knowledge from various sources such as previously labeled data (even when imperfect), heuristics from subject matter experts, business logic, and even the latest foundation models, then scale this knowledge to label large quantities of data.

AI 52

AI AI ML ML 52

Pickl AI

JANUARY 28, 2025

External Data Sources: These can be market research data, social media feeds, or third-party databases that provide additional insights. Data can be structured (e.g., documents and images). The diversity of data sources allows organizations to create a comprehensive view of their operations and market conditions.

Business Intelligence 52

Business Intelligence Business Intelligence ETL Data Lakes 52

phData

JUNE 27, 2023

Using SQL-centric transformations to model data to be deployed. dbt is also great for data lineage and documentation to empower business analysts to make informed decisions on their data. Data Ingestion with Fivetran Fivetran is used to move your source(s) into a centralized space for storage.

SQL 52

SQL Database Data Quality Data Warehouse 52

phData

SEPTEMBER 20, 2023

A data mesh is a conceptual architectural approach for managing data in large organizations. Traditional data management approaches often involve centralizing data in a data warehouse or data lake, leading to challenges like data silos, data ownership issues, and data access and processing bottlenecks.

Data Silos 52

Data Silos Database Data Quality Data Engineering 52

Alation

FEBRUARY 13, 2020

Important evaluation features include capabilities to preview a dataset, see all associated metadata, see user ratings, read user reviews and curator annotations, and view data quality information. Figure 2 illustrates how analysis processes change when analysts work with a data catalog.

Data Lakes 64

Data Lakes Data Analysis Data Analysis Big Data 64

DagsHub

JANUARY 27, 2025

Text Data Labeling Techniques Text data labeling is a nuanced process, where success lies in finding the right balance between human expertise and automatic efficiency for each specific use case. Improve your data quality for better AI Easily curate and annotate your vision, audio, and document data with a single platform.

Machine Learning 52

Machine Learning Machine Learning Natural Language Processing Supervised Learning 52

Pickl AI

MAY 7, 2024

Their tasks encompass: Data Collection and Extraction Identify relevant data sources and gather data from various internal and external systems Extract, transform, and load data into a centralized data warehouse or analytics platform Data Cleaning and Preparation Cleanse and standardize data to ensure accuracy, consistency, and completeness.

Data Analyst 52

Data Analyst Tableau Data Science Data Analysis 52

DagsHub

NOVEMBER 11, 2024

So, we must understand the different unstructured data types and effectively process them to uncover hidden patterns. Textual Data Textual data is one of the most common forms of unstructured data and can be in the format of documents, social media posts, emails, web pages, customer reviews, or conversation logs.

AI 52

AI AI Data Lakes Database 52