Dataversity

MAY 26, 2022

A data lake becomes a data swamp in the absence of comprehensive data quality validation and does not offer a clear link to value creation. Organizations are rapidly adopting the cloud data lake as the data lake of choice, and the need for validating data in real time has become critical.

Data Lakes 52

Data Lakes Machine Learning Machine Learning Data Quality 52

Dataversity

JANUARY 28, 2021

It has been ten years since Pentaho Chief Technology Officer James Dixon coined the term “data lake.” While data warehouse (DWH) systems have had longer existence and recognition, the data industry has embraced the more […]. The post A Bridge Between Data Lakes and Data Warehouses appeared first on DATAVERSITY.

Data Lakes 59

Data Lakes Data Warehouse Data Quality Data Governance 59

Pickl AI

NOVEMBER 15, 2023

Discover the nuanced dissimilarities between Data Lakes and Data Warehouses. Data management in the digital age has become a crucial aspect of businesses, and two prominent concepts in this realm are Data Lakes and Data Warehouses. It acts as a repository for storing all the data.

Data Lakes 52

Data Lakes Data Warehouse Database ETL 52

phData

SEPTEMBER 19, 2023

With the amount of data companies are using growing to unprecedented levels, organizations are grappling with the challenge of efficiently managing and deriving insights from these vast volumes of structured and unstructured data. What is a Data Lake? Consistency of data throughout the data lake.

Data Lakes 52

Data Lakes Data Models Data Modeling Data Warehouse 52

Dataversity

APRIL 23, 2021

Within the Data Management industry, it’s becoming clear that the old model of rounding up massive amounts of data, dumping it into a data lake, and building an API to extract needed information isn’t working. Click to learn more about author Brian Platz.

Database 90

Database Data Lakes Data Silos Data Governance 90

AWS Machine Learning Blog

FEBRUARY 21, 2025

While these models are trained on vast amounts of generic data, they often lack the organization-specific context and up-to-date information needed for accurate responses in business settings. After ingesting the data, you create an agent with specific instructions: agent_instruction = """You are the Amazon Bedrock Agent.

AWS 122

AWS Natural Language Processing Machine Learning Machine Learning 122

AWS Machine Learning Blog

DECEMBER 11, 2024

Heres a sampling of what some of our more active users had to say about their experience with Field Advisor: I use Field Advisor to review executive briefing documents, summarize meetings and outline actions, as well analyze dense information into key points with prompts. Field Advisor continues to enable me to work smarter, not harder.

AWS 105

AWS Database AI AI 105

Data Science Connect

JULY 28, 2023

Data Collection and Integration Data engineers are responsible for designing robust data collection systems that gather information from various IoT devices and sensors. This data is then integrated into centralized databases for further processing and analysis.

Internet of Things 130

Internet of Things Data Engineering Data Engineering Data Engineering 130

AWS Machine Learning Blog

APRIL 3, 2025

Data is one of the most critical assets of many organizations. Theyre constantly seeking ways to use their vast amounts of information to gain competitive advantages. Amazon AppFlow was used to facilitate the smooth and secure transfer of data from various sources into ODAP.

AWS 80

AWS Data Governance Data Silos SQL 80

Dataconomy

SEPTEMBER 4, 2023

Cloud analytics is the art and science of mining insights from data stored in cloud-based platforms. By tapping into the power of cloud technology, organizations can efficiently analyze large datasets, uncover hidden patterns, predict future trends, and make informed decisions to drive their businesses forward.

Analytics 203

Analytics Analytics Big Data Analytics Big Data Analytics 203

Dataversity

AUGUST 15, 2022

If data is the new oil, then high-quality data is the new black gold. Just like with oil, if you don’t have good data quality, you will not get very far. So, what can you do to ensure your data is up to par and […]. You might not even make it out of the starting gate.

Data Observability 52

Data Observability Data Quality Data Lakes Data Warehouse 52

Dataversity

OCTOBER 4, 2022

The rise of data lakes and adjacent patterns such as the data lakehouse has given data teams increased agility and the ability to leverage major amounts of data. Constantly evolving data privacy legislation and the impact of major cybersecurity breaches has led to the call for responsible data […].

Data Lakes 94

Data Lakes Data Governance Data Quality 94

AWS Machine Learning Blog

AUGUST 21, 2024

Amazon DataZone is a data management service that makes it quick and convenient to catalog, discover, share, and govern data stored in AWS, on-premises, and third-party sources. The data lake environment is required to configure an AWS Glue database table, which is used to publish an asset in the Amazon DataZone catalog.

Machine Learning 120

Machine Learning Machine Learning Data Governance ML 120

Tableau

APRIL 18, 2022

Tableau helps strike the necessary balance to access, improve data quality, and prepare and model data for analytics use cases, while writing-back data to data management sources. Analytics data catalog. Review quality and structural information on data and data sources to better monitor and curate for use.

Tableau 102

Tableau Data Quality Analytics Analytics 102

Tableau

APRIL 18, 2022

Tableau helps strike the necessary balance to access, improve data quality, and prepare and model data for analytics use cases, while writing-back data to data management sources. Analytics data catalog. Review quality and structural information on data and data sources to better monitor and curate for use.

Tableau 98

Tableau Data Quality Analytics Analytics 98

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

The MLOps Blog

JUNE 27, 2023

Can you debug system information? 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. Can you compare images?

Machine Learning 134

Machine Learning Machine Learning ML ML 134

Dataversity

DECEMBER 16, 2020

According to IDC, the size of the global datasphere is projected to reach 163 ZB by 2025, leading to the disparate data sources in legacy systems, new system deployments, and the creation of data lakes and data warehouses. Most organizations do not utilize the entirety of the data […].

Data Warehouse 69

Data Warehouse Data Lakes Data Profiling Data Quality 69

Pickl AI

APRIL 21, 2025

Summary: Big Data refers to the vast volumes of structured and unstructured data generated at high speed, requiring specialized tools for storage and processing. Data Science, on the other hand, uses scientific methods and algorithms to analyses this data, extract insights, and inform decisions.

Big Data 52

Big Data Big Data Data Science Machine Learning 52

Pickl AI

DECEMBER 2, 2024

This explosive growth of data is driven by various factors, including the proliferation of internet-connected devices, social media interactions, and the increasing digitization of business processes. Key Takeaways Big Data originates from diverse sources, including IoT and social media.

Big Data 52

Big Data Big Data Data Lakes Apache Hadoop 52

Pickl AI

NOVEMBER 25, 2024

This explosive growth of data is driven by various factors, including the proliferation of internet-connected devices, social media interactions, and the increasing digitization of business processes. Key Takeaways Big Data originates from diverse sources, including IoT and social media.

Big Data 52

Big Data Big Data Data Lakes Apache Hadoop 52

AWS Machine Learning Blog

AUGUST 15, 2024

When SageMaker Data Wrangler finishes importing, you can start transforming the dataset. After you import the dataset, you can first look at the Data Quality Insights Report to see recommendations from SageMaker Canvas on how to improve the data quality and therefore improve the model’s performance.

ML 124

ML ML Data Preparation AWS 124

Alation

JUNE 17, 2021

Lastly, active data governance simplifies stewardship tasks of all kinds. Tehnical stewards have the tools to monitor data quality, access, and access control. A compliance steward is empowered to monitor sensitive data and usage sharing policies at scale. The Data Swamp Problem. The Governance Solution.

Data Governance 98

Data Governance Data Lakes Cloud Data Data Quality 98

Dataversity

MAY 19, 2023

In the early days of business analysis and underwriting, data was managed with simply a pen and paper and, of course, Excel spreadsheets. As technology has advanced, databases, warehouses, and data lakes have enabled information to be collected, stored, and managed electronically.

Data Lakes 52

Data Lakes Database Data Quality 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.

Tableau 102

Tableau Azure Data Quality ML 102

Dataversity

JULY 25, 2024

Over the past few years, the industry has increasingly recognized the need to adopt a data lakehouse architecture because of the inherent benefits. This approach improves data infrastructure costs and reduces time-to-insight by consolidating more data workloads into a single source of truth on the organization’s data lake.

Data Lakes 59

Data Lakes Data Governance Data Quality 59

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

Dataversity

SEPTEMBER 12, 2022

The ways in which we store and manage data have grown exponentially over recent years – and continue to evolve into new paradigms. For much of IT history, though, enterprise data architecture has existed as monolithic, centralized “data lakes.” The post Data Mesh or Data Mess?

Data Lakes 52

Data Lakes Data Quality Data Governance Cloud Data 52

Dataversity

FEBRUARY 10, 2023

For many of these organizations, the path toward becoming more data-driven lies in the power of data lakehouses, which combine elements of data warehouse architecture with data lakes.

Data Lakes 52

Data Lakes Data Warehouse Data Quality Data Governance 52

Pickl AI

OCTOBER 6, 2024

Understanding these methods helps organizations optimize their data workflows for better decision-making. Introduction In today’s data-driven world, efficient data processing is crucial for informed decision-making and business growth. This phase is crucial for enhancing data quality and preparing it for analysis.

ETL 52

ETL Data Warehouse Data Quality Data Lakes 52

IBM Journey to AI blog

AUGUST 4, 2023

Architecture for data democratization Data democratization requires a move away from traditional “data at rest” architecture, which is meant for storing static data. Traditionally, data was seen as information to be put on reserve, only called upon during customer interactions or executing a program.

Data Lakes 73

Data Lakes AI AI Data Governance 73

IBM Journey to AI blog

DECEMBER 16, 2022

So, instead of wandering the aisles in hopes you’ll stumble across the book, you can walk straight to it and get the information you want much faster. An enterprise data catalog does all that a library inventory system does – namely streamlining data discovery and access across data sources – and a lot more.

Data Quality 52

Data Quality Data Governance Data Scientist Data Wrangling 52

Pickl AI

NOVEMBER 4, 2024

The goal is to ensure that data is available, reliable, and accessible for analysis, ultimately driving insights and informed decision-making within organisations. 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.

Data Engineering 52

Data Engineering Data Engineering Data Engineering Data Engineer 52

Dataconomy

FEBRUARY 23, 2023

They are responsible for designing, building, and maintaining the infrastructure and tools needed to manage and process large volumes of data effectively. This involves working closely with data analysts and data scientists to ensure that data is stored, processed, and analyzed efficiently to derive insights that inform decision-making.

Big Data 91

Big Data Big Data Data Engineering Data Engineering 91

Alation

FEBRUARY 13, 2020

A Data Catalog is a collection of metadata, combined with data management and search tools, that helps analysts and other data users to find the data that they need, serves as an inventory of available data, and provides information to evaluate fitness data for intended uses. What is a Data Catalog?

Data Lakes 64

Data Lakes Data Analysis Data Analysis Big Data 64

Pickl AI

JULY 25, 2024

Summary: Data ingestion is the process of collecting, importing, and processing data from diverse sources into a centralised system for analysis. This crucial step enhances data quality, enables real-time insights, and supports informed decision-making.

Apache Kafka 52

Apache Kafka Data Lakes Data Warehouse Data Quality 52

Alation

JULY 19, 2022

Get the data. Explore the data. Model the data. A data catalog can assist directly with every step, but model development. And even then, information from the data catalog can be transferred to a model connector , allowing data scientists to benefit from curated metadata within those platforms.

Data Scientist 59

Data Scientist Data Quality Data Science Data Analyst 59