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 Modeling Data Models Data Warehouse 52

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

Alation

JANUARY 27, 2022

People might not understand the data, the data they chose might not be ideal for their application, or there might be better, more current, or more accurate data available. An effective data governance program ensures data consistency and trustworthiness. It can also help prevent data misuse.

Data Governance 52

Data Governance Analytics Analytics Data Quality 52

AWS Machine Learning Blog

OCTOBER 20, 2023

Recent developments in generative AI models have further sped up the need of ML adoption across industries. However, implementing security, data privacy, and governance controls are still key challenges faced by customers when implementing ML workloads at scale.

ML 131

ML ML AWS Data Lakes 131

Precisely

JUNE 24, 2024

The Precisely team recently had the privilege of hosting a luncheon at the Gartner Data & Analytics Summit in London. It was an engaging gathering of industry leaders from various sectors, who exchanged valuable insights into crucial aspects of data governance, strategy, and innovation.

Analytics 94

Analytics Analytics Data Governance Data Lakes 94

Alation

JANUARY 26, 2023

These data requirements could be satisfied with a strong data governance strategy. Governance can — and should — be the responsibility of every data user, though how that’s achieved will depend on the role within the organization. How can data engineers address these challenges directly?

Data Governance 52

Data Governance Data Engineering Data Engineering Data Engineering 52

Alation

JUNE 14, 2021

And third is what factors CIOs and CISOs should consider when evaluating a catalog – especially one used for data governance. The Role of the CISO in Data Governance and Security. They want CISOs putting in place the data governance needed to actively protect data. So CISOs must protect data.

Data Governance 97

Data Governance Data Lakes Data Classification Data Quality 97

IBM Journey to AI blog

OCTOBER 12, 2023

But the implementation of AI is only one piece of the puzzle. The tasks behind efficient, responsible AI lifecycle management The continuous application of AI and the ability to benefit from its ongoing use require the persistent management of a dynamic and intricate AI lifecycle—and doing so efficiently and responsibly.

AI 93

AI AI Data Scientist Data Governance 93

IBM Journey to AI blog

AUGUST 4, 2023

Data democratization instead refers to the simplification of all processes related to data, from storage architecture to data management to data security. It also requires an organization-wide data governance approach, from adopting new types of employee training to creating new policies for data storage.

Data Lakes 73

Data Lakes AI AI Data Governance 73

Alation

FEBRUARY 1, 2022

A new research report by Ventana Research, Embracing Modern Data Governance , shows that modern data governance programs can drive a significantly higher ROI in a much shorter time span. Historically, data governance has been a manual and restrictive process, making it almost impossible for these programs to succeed.

Data Lakes 52

Data Lakes Data Governance ML ML 52

IBM Journey to AI blog

JUNE 15, 2023

Moreover, increased regulatory requirements make it harder for enterprises to democratize data access and scale the adoption of analytics and artificial intelligence (AI). Against this challenging backdrop, the sense of urgency has never been higher for businesses to leverage AI for competitive advantage.

Data Warehouse 110

Data Warehouse Data Lakes Cloud Data Analytics 110

Tableau

FEBRUARY 14, 2022

For many years, the underlying complexities of AI, paired with a dramatic portrayal in the media as an inevitable replacement for human jobs, created a daunting narrative that made AI difficult for most people to understand, let alone to widely adopt. Now, we’re at an exciting turning point with AI. So what’s changed?

AI 98

AI AI Tableau Data Scientist 98

Tableau

FEBRUARY 14, 2022

For many years, the underlying complexities of AI, paired with a dramatic portrayal in the media as an inevitable replacement for human jobs, created a daunting narrative that made AI difficult for most people to understand, let alone to widely adopt. Now, we’re at an exciting turning point with AI. So what’s changed?

AI 95

AI AI Tableau Data Scientist 95

Dataconomy

SEPTEMBER 4, 2023

Cloud-based business intelligence (BI): Cloud-based BI tools enable organizations to access and analyze data from cloud-based sources and on-premises databases. Machine learning and AI analytics: Machine learning and AI analytics leverage advanced algorithms to automate the analysis of data, discover hidden patterns, and make predictions.

Analytics 203

Analytics Analytics Big Data Analytics Big Data Analytics 203

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

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

Pickl AI

DECEMBER 2, 2024

Key Takeaways Big Data originates from diverse sources, including IoT and social media. Data lakes and cloud storage provide scalable solutions for large datasets. Processing frameworks like Hadoop enable efficient data analysis across clusters. Data Lakes allows for flexibility in handling different data types.

Big Data 52

Big Data Big Data Data Lakes Apache Hadoop 52

Pickl AI

NOVEMBER 25, 2024

Key Takeaways Big Data originates from diverse sources, including IoT and social media. Data lakes and cloud storage provide scalable solutions for large datasets. Processing frameworks like Hadoop enable efficient data analysis across clusters. Data Lakes allows for flexibility in handling different data types.

Big Data 52

Big Data Big Data Data Lakes Apache Hadoop 52

Precisely

JULY 18, 2024

Data management recommendations and data products emerge dynamically from the fabric through automation, activation, and AI/ML analysis of metadata. As data grows exponentially, so do the complexities of managing and leveraging it to fuel AI and analytics.

Data Lakes 52

Data Lakes Data Warehouse Data Governance Machine Learning 52

Precisely

OCTOBER 16, 2023

Big data analytics, IoT, AI, and machine learning are revolutionizing the way businesses create value and competitive advantage. The cloud is especially well-suited to large-scale storage and big data analytics, due in part to its capacity to handle intensive computing requirements at scale.

Analytics 72

Analytics Analytics Big Data Analytics Big Data Analytics 72

Alation

MAY 16, 2023

This makes it easier to compare and contrast information and provides organizations with a unified view of their data. Machine Learning Data pipelines feed all the necessary data into machine learning algorithms, thereby making this branch of Artificial Intelligence (AI) possible.

Data Pipeline 69

Data Pipeline Data Governance Data Lakes Data Warehouse 69

IBM Journey to AI blog

JULY 3, 2024

By 2026, over 80% of enterprises will deploy AI APIs or generative AI applications. AI models and the data on which they’re trained and fine-tuned can elevate applications from generic to impactful, offering tangible value to customers and businesses. Data is exploding, both in volume and in variety.

AI 45

AI AI Data Quality Database 45

Precisely

JANUARY 25, 2024

These systems support containerized applications, virtualization, AI and machine learning, API and cloud connectivity, and more. Today’s cloud systems excel at high-volume data storage, powerful analytics, AI, and software & systems development. They’re also valued for their rock-solid reliability, boasting 99.999% uptime.

Data Governance 69

Data Governance Database Cloud Data Data Lakes 69

Alation

NOVEMBER 2, 2022

We had not seen that in the broader intelligence & data governance market.”. At Databricks, we’re focused on enabling customers to adopt the data lakehouse, and that’s an open data architecture that combines the best of the data warehouse and the data lake into one platform,” Ferguson says. “[The

Data Governance 98

Data Governance Data Lakes Data Warehouse Analytics 98

Alation

APRIL 14, 2022

This is why, when data moves, it’s imperative for organizations to prioritize data discovery. Data discovery is also critical for data governance , which, when ineffective, can actually hinder organizational growth. The Cloud Data Migration Challenge. Data pipeline orchestration. Cloud governance.

Data Governance 59

Data Governance ML ML Cloud Data 59

Alation

APRIL 19, 2022

In that sense, data modernization is synonymous with cloud migration. Modern data architectures, like cloud data warehouses and cloud data lakes , empower more people to leverage analytics for insights more efficiently. What Is the Role of the Cloud in Data Modernization? How to Modernize Data with Alation.

Data Governance 52

Data Governance Cloud Data Database Data Silos 52

phData

AUGUST 5, 2024

Who should have access to sensitive data? How can my analysts discover where data is located? All of these questions describe a concept known as data governance. The Snowflake AI Data Cloud has built an entire blanket of features called Horizon, which tackles all of these questions and more.

Data Governance 52

Data Governance Data Quality Data Lakes ML 52

DataRobot Blog

OCTOBER 3, 2017

This highlights the two companies’ shared vision on self-service data discovery with an emphasis on collaboration and data governance. 2) When data becomes information, many (incremental) use cases surface. DataRobot Data Prep. The post 3 Major Trends at Strata New York 2017 appeared first on DataRobot AI Cloud.

Data Lakes 52

Data Lakes Azure Data Pipeline Hadoop 52

Alation

FEBRUARY 13, 2020

Figure 1 illustrates the typical metadata subjects contained in a data catalog. Figure 1 – Data Catalog Metadata Subjects. Datasets are the files and tables that data workers need to find and access. They may reside in a data lake, warehouse, master data repository, or any other shared data resource.

Data Lakes 64

Data Lakes Data Analysis Data Analysis Big Data 64

DagsHub

OCTOBER 23, 2024

This article will discuss managing unstructured data for AI and ML projects. You will learn the following: Why unstructured data management is necessary for AI and ML projects. How to properly manage unstructured data. The different tools used in unstructured data management. What is Unstructured Data?

Machine Learning 52

Machine Learning Machine Learning Data Lakes AI 52

IBM Journey to AI blog

JANUARY 5, 2023

The first generation of data architectures represented by enterprise data warehouse and business intelligence platforms were characterized by thousands of ETL jobs, tables, and reports that only a small group of specialized data engineers understood, resulting in an under-realized positive impact on the business.

Data Quality 52

Data Quality Data Lakes Data Warehouse Big Data 52

IBM Journey to AI blog

DECEMBER 16, 2022

For example, data catalogs have evolved to deliver governance capabilities like managing data quality and data privacy and compliance. It uses metadata and data management tools to organize all data assets within your organization. This is especially helpful when handling massive amounts of big data.

Data Quality 52

Data Quality Data Governance Data Scientist Data Wrangling 52

Pickl AI

NOVEMBER 4, 2024

Key Takeaways Data Engineering is vital for transforming raw data into actionable insights. Key components include data modelling, warehousing, pipelines, and integration. Effective data governance enhances quality and security throughout the data lifecycle. What is Data Engineering?

Data Engineering 52

Data Engineering Data Engineering Data Engineering Data Engineer 52

Precisely

JUNE 6, 2023

The group kicked off the session by exchanging ideas about what it means to have a modern data architecture. Atif Salam noted that as recently as a year ago, the primary focus in many organizations was on ingesting data and building data lakes.

Data Observability 52

Data Observability Data Lakes Data Quality ETL 52

AWS Machine Learning Blog

FEBRUARY 13, 2024

The following diagram shows two different data scientist teams, from two different AWS accounts, who share and use the same central feature store to select the best features needed to build their ML models. This enhances data accessibility and utilization, allowing teams in different accounts to use shared features for their ML workflows.

AWS 128

AWS ML ML Machine Learning 128

The MLOps Blog

JUNE 27, 2023

With Azure Machine Learning, data scientists can leverage pre-built models, automate machine learning tasks, and seamlessly integrate with other Azure services, making it an efficient and scalable solution for machine learning projects in the cloud. Might be useful Unlike manual, homegrown, or open-source solutions, neptune.ai

Machine Learning 134

Machine Learning Machine Learning ML ML 134

AWS Machine Learning Blog

FEBRUARY 7, 2025

Data Governance Account This account hosts data governance services for data lake, central feature store, and fine-grained data access. Follow the sample code to run an ML experiment pipeline using data stored in an S3 bucket. ML Prod Account This is the production account for new ML models.

ML 63

ML ML Data Scientist AWS 63