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.

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IBM Journey to AI blog

OCTOBER 16, 2023

It includes processes that trace and document the origin of data, models and associated metadata and pipelines for audits. How to scale AL and ML with built-in governance A fit-for-purpose data store built on an open lakehouse architecture allows you to scale AI and ML while providing built-in governance tools.

AI 88

AI AI Data Warehouse ML 88

Mlearning.ai

FEBRUARY 16, 2023

The ultimate need for vast storage spaces manifests in data warehouses: specialized systems that aggregate data coming from numerous sources for centralized management and consistency. In this article, you’ll discover what a Snowflake data warehouse is, its pros and cons, and how to employ it efficiently.

Data Warehouse 52

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Alation

JANUARY 17, 2023

The modern data stack is a combination of various software tools used to collect, process, and store data on a well-integrated cloud-based data platform. It is known to have benefits in handling data due to its robustness, speed, and scalability. A typical modern data stack consists of the following: A data warehouse.

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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. Saurabh Gupta is a Principal Engineer at Zeta Global.

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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. However, this can be time-consuming and prone to human error, leading to misinformation.

Data Lakes 52

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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

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IBM Journey to AI blog

JULY 17, 2023

These encoder-only architecture models are fast and effective for many enterprise NLP tasks, such as classifying customer feedback and extracting information from large documents. While they require task-specific labeled data for fine tuning, they also offer clients the best cost performance trade-off for non-generative use cases.

AI 74

AI AI Machine Learning Machine Learning 74

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

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Dataconomy

APRIL 27, 2023

On the other hand, OLAP systems use a multidimensional database, which is created from multiple relational databases and enables complex queries involving multiple data facts from current and historical data. An OLAP database may also be organized as a data warehouse.

Database 159

Database Data Scientist Data Mining Data Mining 159

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

phData

FEBRUARY 14, 2023

Data integration is essentially the Extract and Load portion of the Extract, Load, and Transform (ELT) process. Data ingestion involves connecting your data sources, including databases, flat files, streaming data, etc, to your data warehouse. Snowflake provides native ways for data ingestion.

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Data Warehouse Azure AWS Database 59

phData

NOVEMBER 28, 2023

How to Get Started with Matillion Data Productivity Cloud That looks unbelievable, but trust me, you can get started with Matillion Data Productivity Cloud from 0 to start your first job in around 5 minutes. Creating Your Account First things first, let’s create your Matillion account in order to deploy your Data Productivity Cloud.

Data Warehouse 52

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phData

AUGUST 9, 2024

Typically, this data is scattered across Excel files on business users’ desktops. Typically, this data is scattered across Excel files on business users’ desktops. They usually operate outside any data governance structure; often, no documentation exists outside the user’s mind.

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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. Data Transformation in the Modern Data Stack.

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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

Alation

OCTOBER 27, 2022

Few actors in the modern data stack have inspired the enthusiasm and fervent support as dbt. This data transformation tool enables data analysts and engineers to transform, test and document data in the cloud data warehouse. But what does this mean from a practitioner perspective?

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phData

JANUARY 24, 2024

Understanding Fivetran Fivetran is a user-friendly, code-free platform enabling customers to easily synchronize their data by automating extraction, transformation, and loading from many sources. Fivetran automates the time-consuming steps of the ELT process so your data engineers can focus on more impactful projects.

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Data Warehouse Data Pipeline Data Governance Cloud Data 52

Alation

MARCH 1, 2022

Through Impact Analysis, users can determine if a problem occurred with data upstream, and locate the impacted data downstream. With robust data lineage, data engineers can find and fix issues fast and prevent them from recurring. Similarly, analysts gain a clear view of how data is created.

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Pickl AI

JUNE 7, 2024

Also Read: Top 10 Data Science tools for 2024. It is a process for moving and managing data from various sources to a central data warehouse. This process ensures that data is accurate, consistent, and usable for analysis and reporting. This process helps organisations manage large volumes of data efficiently.

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phData

JULY 21, 2023

Tableau Architecture Let’s understand a bit more about Tableau architecture which will help in better knowledge of where Tableau data is stored. Data Server : These are basically the databases, files, and data warehouses to which any dashboard connects for the rendering of visuals. Hyper is a compiling query engine.

Tableau 52

Tableau Database Data Engineering Data Engineering 52

phData

JULY 21, 2023

Tableau Architecture Let’s understand a bit more about Tableau architecture which will help in better knowledge of where Tableau data is stored. Data Server : These are basically the databases, files, and data warehouses to which any dashboard connects for the rendering of visuals. Hyper is a compiling query engine.

Tableau 52

Tableau Database Data Engineering Data Engineering 52

Alation

MAY 24, 2022

With the Open Data Quality Initiative, Alation introduces an Open Data Quality Framework (ODQF), which includes a starter kit for data quality partners. This kit offers an open DQ API, developer documentation, onboarding, integration best practices, and co-marketing support.

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Data Quality Data Governance ETL Data Observability 98

phData

MARCH 29, 2024

Founded in 2014 by three leading cloud engineers, phData focuses on solving real-world data engineering, operations, and advanced analytics problems with the best cloud platforms and products. Over the years, one of our primary focuses became Snowflake and migrating customers to this leading cloud data platform.

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 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

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

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.

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Data Silos Database Data Quality Data Engineering 52

Alation

JUNE 20, 2023

Alation: And you likely had plenty of data even before the acquisition. The challenge wasn’t that we had nothing to document. Data from any other brands we acquired or built were based on the same schema, so an engineering team looking for data would say, “We know about where it is, but we don’t know exactly where it is.”

Data Governance 52

Data Governance Database SQL Data Engineering 52

DagsHub

JANUARY 27, 2025

The approach has shown exceptional results in specialized domains such as legal document classification and medical text analysis, where nuanced interpretation is crucial [ reference ]. Documentation Requirements Documentation serves both as a historical record and a living guide.

Machine Learning 52

Machine Learning Machine Learning Natural Language Processing Supervised Learning 52

Alation

SEPTEMBER 7, 2021

With Snowflake, data stewards have a choice to leverage Snowflake’s governance policies. First, stewards are dependent on data warehouse admins to provide information and to create and edit enforcement policies in Snowflake. Alation’s data lineage helps organizations to secure their data in the Snowflake Data Cloud.

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Data Governance Data Scientist Data Quality Data Profiling 59

Alation

APRIL 6, 2023

Data governance is traditionally applied to structured data assets that are most often found in databases and information systems. This blog focuses on governing spreadsheets that contain data, information, and metadata, and must themselves be governed. There are others that consider spreadsheets to be trouble.

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phData

MAY 25, 2023

One of the easiest ways for Snowflake to achieve this is to have analytics solutions query their data warehouse in real-time (also known as DirectQuery). For more information on composite models, check out Microsoft’s official documentation. This ensures the maximum amount of Snowflake consumption possible.

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Mlearning.ai

JULY 10, 2023

Without partitioning, daily data activities will cost your company a fortune and a moment will come where the cost advantage of GCP BigQuery becomes questionable. There are other options you can place, and as usual, I suggest you to reference the official documentation to learn more.

SQL 52

SQL Database Database Administration Data Lakes 52

Pickl AI

SEPTEMBER 5, 2024

Data Preparation: Cleaning, transforming, and preparing data for analysis and modelling. Collaborating with Teams: Working with data engineers, analysts, and stakeholders to ensure data solutions meet business needs. Start by setting up your own Azure account and experimenting with various services.

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phData

FEBRUARY 8, 2024

Data Modeling, dbt has gradually emerged as a powerful tool that largely simplifies the process of building and handling data pipelines. dbt is an open-source command-line tool that allows data engineers to transform, test, and document the data into one single hub which follows the best practices of software engineering.

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phData

OCTOBER 25, 2024

Data Quality Monitoring implements quality checks in operational data processes to ensure that the data meets pre-defined standards and business rules. This results in poor credibility and data consistency after some time, leading businesses to mistrust the data pipelines and processes.

Data Quality 52

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phData

MAY 6, 2024

Another benefit of deterministic matching is that the process to build these identities is relatively simple, and tools your teams might already use, like SQL and dbt , can efficiently manage this process within your cloud data warehouse. However, targeted web advertising may only require linkage to a browser or device ID.

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