ODSC - Open Data Science

SEPTEMBER 29, 2023

A 2019 survey by McKinsey on global data transformation revealed that 30 percent of total time spent by enterprise IT teams was spent on non-value-added tasks related to poor data quality and availability. The data lake can then refine, enrich, index, and analyze that data. and various countries in Europe.

Data Lakes 52

Data Lakes Clustering Big Data Big Data 52

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.

AWS 106

AWS Database AI AI 106

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

AWS Machine Learning Blog

AUGUST 21, 2023

You can streamline the process of feature engineering and data preparation with SageMaker Data Wrangler and finish each stage of the data preparation workflow (including data selection, purification, exploration, visualization, and processing at scale) within a single visual interface.

AWS 98

AWS Data Lakes Clustering Data Preparation 98

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

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

APRIL 21, 2025

Real-World Example: Healthcare systems manage a huge variety of data: structured patient demographics, semi-structured lab reports, and unstructured doctor’s notes, medical images (X-rays, MRIs), and even data from wearable health monitors. Ensuring data quality and accuracy is a major challenge.

Big Data 52

Big Data Big Data Data Science Machine Learning 52

Pickl AI

NOVEMBER 4, 2024

Role of Data Engineers in the Data Ecosystem Data Engineers play a crucial role in the data ecosystem by bridging the gap between raw data and actionable insights. They are responsible for building and maintaining data architectures, which include databases, data warehouses, and data lakes.

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52

IBM Journey to AI blog

AUGUST 4, 2023

By leveraging data services and APIs, a data fabric can also pull together data from legacy systems, data lakes, data warehouses and SQL databases, providing a holistic view into business performance. Then, it applies these insights to automate and orchestrate the data lifecycle.

Data Lakes 73

Data Lakes AI AI Data Governance 73

Pickl AI

OCTOBER 6, 2024

This phase is crucial for enhancing data quality and preparing it for analysis. Transformation involves various activities that help convert raw data into a format suitable for reporting and analytics. Normalisation: Standardising data formats and structures, ensuring consistency across various data sources.

ETL 52

ETL Data Warehouse Data Quality Data Lakes 52

Alation

JULY 19, 2022

Increasingly, data catalogs not only provide the location of data assets, but also the means to retrieve them. A data scientist can use the catalog to identify several assets that might be relevant to their question and then use a built-in SQL query editor, like Compose, to access the data.

Data Scientist 59

Data Scientist Data Quality Data Science Data Analyst 59

IBM Journey to AI blog

JULY 3, 2024

This includes integration with your data warehouse engines, which now must balance real-time data processing and decision-making with cost-effective object storage, open source technologies and a shared metadata layer to share data seamlessly with your data lakehouse.

AI 45

AI AI Data Quality Database 45

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

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

Alation

SEPTEMBER 23, 2021

Guided Navigation – Guided navigation provides intelligent suggestions, which guide correct usage of data. Behavioral intelligence, embedded in the catalog, learns from user behavior to enforce best practices through features like data quality flags, which help folks stay compliant as they use data.

Data Preparation 52

Data Preparation SQL Data Governance Data Analysis 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 52

Tableau Azure Data Quality ML 52

Alation

OCTOBER 19, 2022

Alation’s usability goes well beyond data discovery (used by 81 percent of our customers), data governance (74 percent), and data stewardship / data quality management (74 percent). The report states that 35 percent use it to support data warehousing / BI and the same percentage for data lake processes. “It

Data Governance 52

Data Governance Data Quality Data Lakes Data Observability 52

Pickl AI

JULY 8, 2024

Organisations leverage diverse methods to gather data, including: Direct Data Capture: Real-time collection from sensors, devices, or web services. Database Extraction: Retrieval from structured databases using query languages like SQL. NoSQL Databases: Flexible, scalable solutions for unstructured or semi-structured data.

Data Pipeline 52

Data Pipeline Data Quality Database Apache Kafka 52

Pickl AI

APRIL 9, 2025

This includes operations like data validation, data cleansing, data aggregation, and data normalization. The goal is to ensure that the data is consistent and ready for analysis. Loading : Storing the transformed data in a target system like a data warehouse, data lake, or even a database.

ETL 52

ETL Data Warehouse AWS Business Intelligence 52

Pickl AI

OCTOBER 17, 2024

ETL facilitates Data Analytics by transforming raw data into meaningful insights, empowering businesses to uncover trends, track performance, and make strategic decisions. ETL also enhances data quality and consistency by performing necessary data cleansing and validation during the transformation stage.

ETL 52

ETL Data Warehouse SQL Data Quality 52

phData

AUGUST 5, 2024

Horizon addresses key aspects of data governance, including: Compliance Security Access Privacy Interoperability Throughout the remainder of this blog, we will dive deeper into each of the above components and take a look at the ways in which Horizon can help. We will begin with compliance.

Data Governance 52

Data Governance Data Quality Data Lakes ML 52

Pickl AI

JANUARY 28, 2025

This involves several key processes: Extract, Transform, Load (ETL): The ETL process extracts data from different sources, transforms it into a suitable format by cleaning and enriching it, and then loads it into a data warehouse or data lake. Data Lakes: These store raw, unprocessed data in its original format.

Business Intelligence 52

Business Intelligence Business Intelligence ETL Data Lakes 52

The MLOps Blog

MARCH 15, 2023

Data Processing : You need to save the processed data through computations such as aggregation, filtering and sorting. Data Storage : To store this processed data to retrieve it over time – be it a data warehouse or a data lake. This ensures that the data is accurate, consistent, and reliable.

Data Pipeline 59

Data Pipeline ETL SQL Data Quality 59

AWS Machine Learning Blog

AUGUST 4, 2023

In the data flow view, you can now see a new node added to the visual graph. For more information on how you can use SageMaker Data Wrangler to create Data Quality and Insights Reports, refer to Get Insights On Data and Data Quality. SageMaker Data Wrangler offers over 300 built-in transformations.

ML 97

ML ML AWS AI 97

IBM Journey to AI blog

MARCH 14, 2024

Businesses face significant hurdles when preparing data for artificial intelligence (AI) applications. The existence of data silos and duplication, alongside apprehensions regarding data quality, presents a multifaceted environment for organizations to manage.

AWS 93

AWS Database ETL AI 93

Pickl AI

AUGUST 9, 2024

NoSQL Databases These databases, such as MongoDB, Cassandra, and HBase, are designed to handle unstructured and semi-structured data, providing flexibility and scalability for modern applications. Understanding the differences between SQL and NoSQL databases is crucial for students.

Big Data 52

Big Data Big Data Big Data Analytics Big Data Analytics 52

DagsHub

OCTOBER 23, 2024

Here’s the structured equivalent of this same data in tabular form: With structured data, you can use query languages like SQL to extract and interpret information. In contrast, such traditional query languages struggle to interpret unstructured data. It also aids in identifying the source of any data quality issues.

Machine Learning 52

Machine Learning Machine Learning Data Lakes AI 52

Pickl AI

AUGUST 1, 2023

Key Components of Data Engineering Data Ingestion : Gathering data from various sources, such as databases, APIs, files, and streaming platforms, and bringing it into the data infrastructure. Data Processing: Performing computations, aggregations, and other data operations to generate valuable insights from the data.

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52

Alation

NOVEMBER 28, 2022

It’s impossible for data teams to assure the data quality of such spreadsheets and govern them all effectively. If unaddressed, this chaos can lead to data quality, compliance, and security issues. In an enterprise, there may be thousands of spreadsheets used for critical business decisions.

Data Governance 52

Data Governance Database Data Quality Data Lakes 52

phData

MAY 6, 2024

Data Quality Next, dive into the details of your data. 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.

Data Lakes 52

Data Lakes Data Warehouse Cloud Data SQL 52

The MLOps Blog

MARCH 21, 2023

Olalekan said that most of the random people they talked to initially wanted a platform to handle data quality better, but after the survey, he found out that this was the fifth most crucial need. I have worked with customers where R and SQL were the first-class languages of their data science community.

Machine Learning 69

Machine Learning Machine Learning Data Scientist ML 69

AWS Machine Learning Blog

JANUARY 26, 2024

Define strict data ingress and egress rules to help protect against manipulation and exfiltration using VPCs with AWS Network Firewall policies. With Security Lake, you can get a more complete understanding of your security data across your entire organization.

AWS 139

AWS ML ML AI 139

phData

SEPTEMBER 27, 2024

Some modern CDPs are starting to incorporate these concepts, allowing for more flexible and evolving customer data models. It also requires a shift in how we query our customer data. Instead of simple SQL queries, we often need to use more complex temporal query languages or rely on derived views for simpler querying.

Data Modeling 52

Data Modeling Data Models Apache Kafka Data Lakes 52

ODSC - Open Data Science

APRIL 25, 2025

One of the main drivers for this problem is that most analytic systems are built within the context of a unified SQL environment. Getting all the data together, in one place, and integrated is generally the main goal of ourwork. Unfortunately in analytic systems, we have been doing little other than tight coupling for decades.

Data Engineering 52

Data Engineering Data Engineering Data Engineering Data Engineer 52