Alation

MAY 24, 2022

In a sea of questionable data, how do you know what to trust? Data quality tells you the answer. It signals what data is trustworthy, reliable, and safe to use. It empowers engineers to oversee data pipelines that deliver trusted data to the wider organization. Today, as part of its 2022.2

Data Quality 52

Data Quality Data Pipeline DataOps Analytics 52

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

Data Science Dojo

JULY 6, 2023

These tools provide data engineers with the necessary capabilities to efficiently extract, transform, and load (ETL) data, build data pipelines, and prepare data for analysis and consumption by other applications. Essential data engineering tools for 2023 Top 10 data engineering tools to watch out for in 2023 1.

Data Engineer 195

Data Engineer Data Engineering Data Engineering Data Engineering 195

Pickl AI

DECEMBER 15, 2024

Explore popular data warehousing tools and their features. Emphasise the importance of data quality and security measures. Data Warehouse Interview Questions and Answers Explore essential data warehouse interview questions and answers to enhance your preparation for 2025. Explain the Concept of a Data Mart.

Data Warehouse 52

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Data Science Dojo

OCTOBER 10, 2023

Link to event -> IMPACT 2o23 Key topics covered IMPACT brings together the data community to showcase the latest and greatest trends, technologies, and processes in data quality, large-language models, data and AI governance, and of course, data observability. Link to event -> Live!

AI 243

AI AI Data Observability Artificial Intelligence 243

Dataconomy

OCTOBER 8, 2024

Some of the challenges include discrepancies in the data, inaccurate data, corrupted data and security vulnerabilities. Adding to these headaches, it can be tricky for developers to identify the source of their inaccurate or corrupted data, which complicates efforts to maintain data quality.

Data Pipeline 132

Data Pipeline AI AI Data Warehouse 132

Smart Data Collective

OCTOBER 20, 2020

It may seem like a considerable investment, but beefing up your defenses prevents critical data from falling into the wrong hands. Consider adding a web application firewall that prevents the injection of damaging SQL commands that will destabilize your database. More importantly, you need to cleanse your SQL server of old code.

Big Data 130

Big Data Big Data Database Database Administration 130

Smart Data Collective

APRIL 29, 2020

Redshift is the product for data warehousing, and Athena provides SQL data analytics. AWS Glue helps users to build data catalogues, and Quicksight provides data visualisation and dashboard construction. Dataform is a data transformation platform that is based on SQL.

Data Warehouse 98

Data Warehouse Azure SQL ETL 98

AWS Machine Learning Blog

DECEMBER 11, 2024

Using the services built-in source connectors standardizes and simplifies the work needed to maintain data quality and manage the overall data lifecycle. This will enable teams across all roles to ask detailed questions about their customer and partner accounts, territories, leads and contacts, and sales pipeline.

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AWS Machine Learning Blog

OCTOBER 9, 2024

The service, which was launched in March 2021, predates several popular AWS offerings that have anomaly detection, such as Amazon OpenSearch , Amazon CloudWatch , AWS Glue Data Quality , Amazon Redshift ML , and Amazon QuickSight. You can review the recommendations and augment rules from over 25 included data quality rules.

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AWS ML ML Data Quality 82

The MLOps Blog

JUNE 27, 2023

Data quality control: Robust dataset labeling and annotation tools incorporate quality control mechanisms such as inter-annotator agreement analysis, review workflows, and data validation checks to ensure the accuracy and reliability of annotations. Data monitoring tools help monitor the quality of the data.

Machine Learning 134

Machine Learning Machine Learning ML ML 134

Data Science Dojo

JANUARY 12, 2023

Insights of data warehouse A data warehouse is a database designed for the analysis of relational data from corporate applications and transactional systems. The results of rapid SQL queries are often utilized for operational reporting and analysis; thus, the data structure and schema are set in advance to optimize for this.

Data Lakes 221

Data Lakes Data Warehouse Hadoop Machine Learning 221

phData

FEBRUARY 2, 2024

This evolved into the phData Toolkit , a collection of high-quality data applications to help you migrate, validate, optimize, and secure your data. Learn more about the phData Toolkit What is the Data Source Tool? This would be ideal to run regularly to track what your database looked like historically.

SQL 52

SQL Database Data Quality Data Engineering 52

Pickl AI

DECEMBER 25, 2024

Descriptive analytics is a fundamental method that summarizes past data using tools like Excel or SQL to generate reports. Techniques such as data cleansing, aggregation, and trend analysis play a critical role in ensuring data quality and relevance. Data Scientists rely on technical proficiency.

Data Science 52

Data Science Analytics Analytics Data Scientist 52

Tableau

FEBRUARY 17, 2021

You can now connect to your data in Azure SQL Database (with Azure Active Directory) and Azure Data Lake Gen 2. First, we’ve added automated data quality warnings (DQW) , which are automatically created when an extract refresh or Tableau Prep flow run fails. Microsoft Azure connectivity improvements.

Tableau 102

Tableau Azure Data Quality ML 102

ODSC - Open Data Science

MARCH 13, 2023

Some of the issues make perfect sense as they relate to data quality, with common issues being bad/unclean data and data bias. What are the biggest challenges in machine learning? select all that apply) Related to the previous question, these are a few issues faced in machine learning.

Machine Learning 94

Machine Learning Machine Learning Data Wrangling Data Science 94

Pickl AI

MARCH 3, 2025

Summary: Business Intelligence Analysts transform raw data into actionable insights. They use tools and techniques to analyse data, create reports, and support strategic decisions. Key skills include SQL, data visualization, and business acumen. Introduction We are living in an era defined by data.

Business Intelligence 52

Business Intelligence Business Intelligence Data Analyst Data Visualization 52

phData

MARCH 1, 2023

The first one we want to talk about is the Toolkit SQL analyze command. When customers are looking to perform a migration, one of the first things that needs to occur is an assessment of the level of effort to migrate existing data definition language (DDL) and data markup language (DML).

SQL 52

SQL Data Pipeline Data Quality Database 52

Precisely

AUGUST 15, 2024

Address common challenges in managing SAP master data by using AI tools to automate SAP processes and ensure data quality. Create an AI-driven data and process improvement loop to continuously enhance your business operations. Think about material master data, for example. Data creation and management processes.

AI 64

AI AI Data Quality Data Engineering 64

Smart Data Collective

SEPTEMBER 26, 2021

The way in which you store data impacts ease of access, use, not to mention security. Choosing the right data storage model for your requirements is paramount. There are countless implementations to choose from, including SQL and NoSQL databases. A NoSQl database can use documents for the storage and retrieval of data.

Database 130

Database Data Visualization Big Data Big Data 130

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

Pickl AI

NOVEMBER 4, 2024

Key components of data warehousing include: ETL Processes: ETL stands for Extract, Transform, Load. This process involves extracting data from multiple sources, transforming it into a consistent format, and loading it into the data warehouse. ETL is vital for ensuring data quality and integrity.

Data Engineer 52

Data Engineer Data Engineering Data Engineering Data Engineering 52

Dataconomy

AUGUST 7, 2023

Beyond its performance merits, Couchbase also integrates Big Data and SQL functionalities, positioning it as a multifaceted solution for complex AI and ML tasks. This blend of features makes it an attractive option for applications requiring real-time data access and analytical capabilities.

Database 168

Database AI AI ML 168

phData

AUGUST 10, 2023

That said, dbt provides the ability to generate data vault models and also allows you to write your data transformations using SQL and code-reusable macros powered by Jinja2 to run your data pipelines in a clean and efficient way. The most important reason for using DBT in Data Vault 2.0

SQL 52

SQL Data Observability Data Quality Data Pipeline 52

phData

AUGUST 22, 2024

Snowflake Cortex stood out as the ideal choice for powering the model due to its direct access to data, intuitive functionality, and exceptional performance in handling SQL tasks. I used a demo project that I frequently work with and introduced syntax errors and data quality problems.

SQL 52

SQL Data Quality Python Data Warehouse 52

IBM Journey to AI blog

MAY 15, 2024

Organizations require reliable data for robust AI models and accurate insights, yet the current technology landscape presents unparalleled data quality challenges. With a multicloud data strategy, organizations need to optimize for data gravity and data locality.

Data Pipeline 85

Data Pipeline ETL SQL Database 85

Alation

JUNE 30, 2021

Intelligent SQL Editor. Compose, Alation’s intelligent SQL editor, offers a number of user-friendly features GigaOm highlights as useful: “Compose [is] Alation’s intelligent SQL query tool, which walks users through writing SQL queries, providing inline ML-based recommendations called SmartSuggestions.”.

SQL 52

SQL ML ML Data Governance 52

Snorkel AI

JUNE 2, 2023

As users integrate more sources of knowledge, the platform enables them to rapidly improve training data quality and model performance using integrated error analysis tools. This connector makes clients’ Databricks data accessible to Snorkel Flow with just a few clicks. Enter Databricks SQL connection details and credentials.

SQL 52

SQL Machine Learning Machine Learning ML 52

Snorkel AI

JUNE 2, 2023

As users integrate more sources of knowledge, the platform enables them to rapidly improve training data quality and model performance using integrated error analysis tools. This connector makes clients’ Databricks data accessible to Snorkel Flow with just a few clicks. Enter Databricks SQL connection details and credentials.

SQL 52

SQL Machine Learning Machine Learning ML 52

ODSC - Open Data Science

APRIL 3, 2023

Skills like effective verbal and written communication will help back up the numbers, while data visualization (specific frameworks in the next section) can help you tell a complete story. Data Wrangling: Data Quality, ETL, Databases, Big Data The modern data analyst is expected to be able to source and retrieve their own data for analysis.

Analytics 52

Analytics Analytics Data Analyst Data Science 52

Towards AI

AUGUST 27, 2024

Additionally, supervised data in chat format was used to align the model with human preferences on instruct-following, truthfulness, honesty, and helpfulness. The focus on data quality was paramount. A lot of time is spent on gathering and cleaning the training data for LLMs, yet the end result is often still raw/dirty.

AI 105

AI AI SQL Data Quality 105

phData

FEBRUARY 5, 2024

Setting up the Information Architecture Setting up an information architecture during migration to Snowflake poses challenges due to the need to align existing data structures, types, and sources with Snowflake’s multi-cluster, multi-tier architecture. Moving historical data from a legacy system to Snowflake poses several challenges.

SQL 52

SQL Database Data Quality Data Warehouse 52

AWS Machine Learning Blog

APRIL 24, 2023

Data Wrangler has more than 300 preconfigured data transformations that can effectively be used in transforming the data. In addition, you can write custom transformation in PySpark, SQL, and pandas. Refer to Get Insights On Data and Data Quality for more information. For Target column , choose label.

Data Quality 76

Data Quality Machine Learning Machine Learning Deep Learning 76

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

Pickl AI

JULY 18, 2023

SQL: Mastering Data Manipulation Structured Query Language (SQL) is a language designed specifically for managing and manipulating databases. While it may not be a traditional programming language, SQL plays a crucial role in Data Science by enabling efficient querying and extraction of data from databases.

Data Science 52

Data Science SQL Data Scientist Python 52

phData

MAY 14, 2024

There are many tools in the Toolkit, but here are some of the highlights that help the most with migrations: SQL Translation Automated translation is indispensable when migrating between data platforms. The SQL Translation application instantly converts queries from one SQL dialect to another.

SQL 52

SQL Data Warehouse Data Engineering Data Engineering 52

Alation

AUGUST 30, 2022

With Alation Anywhere launching in beta, we will meet people where they are, helping to deliver context and trustworthiness of data, from and across the modern data stack, starting with Tableau. With this integration, Alation descriptions and data quality flags of warnings and deprecations will propagate to Tableau.

Data Governance 52

Data Governance Tableau Data Quality Data Analyst 52