AWS Big Data

NOVEMBER 29, 2023

This includes tools to help you customize your foundation models, and new services and features to build a strong data foundation to fuel your generative AI applications. Customizing foundation models The need for data is quite obvious if you are building your own foundation models (FMs).

Data Warehouse 109

Data Warehouse Data Lake Data Integration Dashboards 109

AWS Big Data

APRIL 6, 2023

In this post, Morningstar’s Data Lake Team Leads discuss how they utilized tag-based access control in their data lake with AWS Lake Formation and enabled similar controls in Amazon Redshift. This way, our existing data lake consumers could easily transition to Amazon Redshift.

Data Warehouse 83

Data Warehouse Data Lake Management Data-driven 83

AWS Big Data

MARCH 25, 2024

Foundation models (FMs) are large machine learning (ML) models trained on a broad spectrum of unlabeled and generalized datasets. This scale and general-purpose adaptability are what makes FMs different from traditional ML models. FMs are multimodal; they work with different data types such as text, video, audio, and images.

Data Lake 88

Data Lake Unstructured Data Management Modeling 88

AWS Big Data

MARCH 7, 2023

A data hub contains data at multiple levels of granularity and is often not integrated. It differs from a data lake by offering data that is pre-validated and standardized, allowing for simpler consumption by users. Data hubs and data lakes can coexist in an organization, complementing each other.

Analytics 70

Analytics Data Warehouse Data Lake Metadata 70

AWS Big Data

DECEMBER 21, 2023

To bring their customers the best deals and user experience, smava follows the modern data architecture principles with a data lake as a scalable, durable data store and purpose-built data stores for analytical processing and data consumption. This is the Data Mart stage.

Data Lake 87

Data Lake Data Warehouse Data-driven B2B 87

AWS Big Data

NOVEMBER 16, 2023

Amazon Redshift is a popular cloud data warehouse, offering a fully managed cloud-based service that seamlessly integrates with an organization’s Amazon Simple Storage Service (Amazon S3) data lake, real-time streams, machine learning (ML) workflows, transactional workflows, and much more—all while providing up to 7.9x

Enterprise 82

Enterprise Data Warehouse Snapshot Cost-Benefit 82

AWS Big Data

MARCH 27, 2023

Developers, data scientists, and analysts can work across databases, data warehouses, and data lakes to build reporting and dashboarding applications, perform real-time analytics, share and collaborate on data, and even build and train machine learning (ML) models with Redshift Serverless.

Data Warehouse 83

Data Warehouse Management Snapshot Data Lake 83

IBM Big Data Hub

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. Technical metadata to describe schemas, indexes and other database objects.

Metadata 52

Metadata Data Quality Data-driven Data Governance 52

AWS Big Data

JULY 28, 2023

Data mapping involves identifying and documenting the flow of personal data in an organization. It helps organizations understand how personal data moves through their systems, where it is stored, and how it is processed. Note that putting a comprehensive data strategy in place is not in scope for this post.

Snapshot 81

Snapshot Metadata Measurement Data Warehouse 81

Andrew White

OCTOBER 22, 2021

Monetization/Link data to outcome (value pyramid) business value of data/business impact 20. Business Information Model/Arch compared to classic enterprise data model and how to relate it to catalogs and marketplaces and enterprise data models 13. Data Management Infrastructure/Data Fabric 5.

IT 52

IT Data Lake Strategy Data Science 52

Cloudera

JANUARY 15, 2021

Some examples of recent optimizations in Impala include: New multithreading model (see dedicated blog post ). Remote read optimizations: IMPALA-8341: Data cache for remote reads. As part of the broader CDP, CDW participates in a centralized security and governance model managed by CDP’s Shared Data Experience (SDX).

Data Warehouse 91

Data Warehouse Cost-Benefit Consulting Interactive 91

Ontotext

MARCH 8, 2023

With the size of data and dropping attention spans of online users, digital personalization has become one of the top priorities for companies’ business models. As such, most large financial organizations have moved their data to a data lake or a data warehouse to understand and manage financial risk in one place.

Enterprise 52

Enterprise Knowledge Discovery Risk Data-driven 52

Domino Data Lab

APRIL 3, 2019

Data governance shows up as the fourth-most-popular kind of solution that enterprise teams were adopting or evaluating during 2019. That’s a lot of priorities – especially when you group together closely related items such as data lineage and metadata management which rank nearby. in lieu of simply landing in a data lake.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

Cloudera

NOVEMBER 10, 2021

In CDH, Apache Sentry provided a stand-alone authorization module for Hadoop SQL components like Apache Hive and Apache Impala as well as other services like Apache Solr, Apache Kafka, and HDFS (limited to Hive table data). Furthermore, Apache Ranger now supports Public Cloud objects stores like Amazon S3 and Azure Data Lake Store (ADLS).

Data Lake 75

Data Lake Management Metadata Modeling 75

Alation

FEBRUARY 20, 2020

Architecturally the introduction of Hadoop, a file system designed to store massive amounts of data, radically affected the cost model of data. Organizationally the innovation of self-service analytics, pioneered by Tableau and Qlik, fundamentally transformed the user model for data analysis.

Data Lake 52

Data Lake Metadata Structured Data Big Data 52

bridgei2i

MARCH 3, 2021

Also, ML-ops or machine learning operationalization approaches to bridge the gap between sandbox and production pipelines, while ensuring model lifecycle management from raw data to predictive, as well as prescriptive, insights integration. Pavan: I think Prinkan, you’ve touched upon the concept of experimenting with ML technologies.

Enterprise 98

Enterprise Digital Transformation Data-driven Interactive 98

Domino Data Lab

AUGUST 8, 2019

Across the board, organizations struggle with hiring enough data scientists. Meanwhile, many organizations also struggle with “late in the pipeline issues” on model deployment in production and related compliance. then building machine learning models to recommend methods and potential collaborators to scientists.

Data Science 71

Data Science Machine Learning Data Governance Statistics 71

IBM Big Data Hub

OCTOBER 4, 2023

A data lakehouse architecture combines the performance of data warehouses with the flexibility of data lakes, to address the challenges of today’s complex data landscape and scale AI. New insights and relationships are found in this combination. All of this supports the use of AI.

Data Lake 83

Data Lake Metadata Cost-Benefit Data Warehouse 83

AWS Big Data

OCTOBER 25, 2023

Unstructured data is information that doesn’t conform to a predefined schema or isn’t organized according to a preset data model. Text, images, audio, and videos are common examples of unstructured data. Therefore, there is a need to being able to analyze and extract value from the data economically and flexibly.

Unstructured Data 117

Unstructured Data Metadata Management Analytics 117

CIO Business Intelligence

DECEMBER 21, 2022

BI software helps companies do just that by shepherding the right data into analytical reports and visualizations so that users can make informed decisions. To gain employee buy-in, Stout’s team builds BI dashboards to show them how they can easily connect to and interact with their data, as well as visualize it in a meaningful way.

IT 125

IT Business Intelligence Sales Key Performance Indicator 125

Alation

JULY 19, 2022

Across the country, data scientists have an unemployment rate of 2% and command an average salary of nearly $100,000. As they attempt to put machine learning models into production, data science teams encounter many of the same hurdles that plagued data analytics teams in years past: Finding trusted, valuable data is time-consuming.

Metadata 59

Metadata Data Quality Statistics Data Science 59

IBM Big Data Hub

APRIL 27, 2022

Gartner defines a data fabric as “a design concept that serves as an integrated layer of data and connecting processes. The data fabric architectural approach can simplify data access in an organization and facilitate self-service data consumption at scale.

Management 85

Management Metadata Data Architecture Data Lake 85

IBM Big Data Hub

JULY 17, 2023

is our enterprise-ready next-generation studio for AI builders, bringing together traditional machine learning (ML) and new generative AI capabilities powered by foundation models. With watsonx.ai, businesses can effectively train, validate, tune and deploy AI models with confidence and at scale across their enterprise. IBM watsonx.ai

Machine Learning 65

Machine Learning Data Warehouse Modeling Cost-Benefit 65

Cloudera

JANUARY 21, 2021

With CDW, as an integrated service of CDP, your line of business gets immediate resources needed for faster application launches and expedited data access, all while protecting the company’s multi-year investment in centralized data management, security, and governance. Proprietary file formats mean no one else is invited in!

Data Lake 93

Data Lake Data Warehouse IT Analytics 93

IBM Big Data Hub

OCTOBER 12, 2023

Connecting AI models to a myriad of data sources across cloud and on-premises environments AI models rely on vast amounts of data for training. Once trained and deployed, models also need reliable access to historical and real-time data to generate content, make recommendations, detect errors, send proactive alerts, etc.

Cost-Benefit 81

Cost-Benefit Metadata Data Governance Modeling 81

Alation

APRIL 14, 2022

Data discovery is also critical for data governance , which, when ineffective, can actually hinder organizational growth. And, as organizations progress and grow, “data drift” starts to impact data usage, models, and your business. The Cloud Data Migration Challenge. Visual Profiling. Scheduling.

Metadata 59

Metadata Data Governance Modeling Data-driven 59

Cloudera

MARCH 23, 2022

For example, a Jupyter notebook in CML, can use Spark or Python framework to directly access an Iceberg table to build a forecast model, while new data is ingested via NiFi flows, and a SQL analyst monitors revenue targets using Data Visualization. Simplify data management . 2: Open formats. 3: Open Performance.

Metadata 89

Metadata Data Architecture Machine Learning Cost-Benefit 89

Cloudera

MAY 19, 2021

RAPIDS on the Cloudera Data Platform comes pre-configured with all the necessary libraries and dependencies to bring the power of RAPIDS to your projects. RAPIDS brings the power of GPU compute to standard Data Science operations, be it exploratory data analysis, feature engineering or model building. Data Ingestion.

Machine Learning 137

Machine Learning Data Science Data Lake Modeling 137

Andrew White

JANUARY 11, 2021

Where does the Data Architect role fits in the Operational Model ? Assuming a data architect helps model and guide and assist D&A then they play a key role. As such any Data and Analytics strategy needs to incorporate data sovereignty as per of its D&A governance program. Try some gamification?

Data Analytics 52

Data Analytics Analytics Data-driven Finance 52

Alation

JUNE 21, 2022

Analysts didn’t just want to catalog data sources, they wanted to include dashboards, reports, and visualizations. Why start with a data source and build a visualization, if you can just find a visualization that already exists, complete with metadata about it? Data engineers want to catalog data pipelines.

Metadata 52

Metadata Data Quality Visualization Data Lake 52

CIO Business Intelligence

MARCH 6, 2023

Advancements in analytics and AI as well as support for unstructured data in centralized data lakes are key benefits of doing business in the cloud, and Shutterstock is capitalizing on its cloud foundation, creating new revenue streams and business models using the cloud and data lakes as key components of its innovation platform.

Data Lake 61

Data Lake Cost-Benefit Recreation/Entertainment Experimentation 61

Alation

FEBRUARY 17, 2023

Reichental describes data governance as the overarching layer that empowers people to manage data well ; as such, it is focused on roles & responsibilities, policies, definitions, metrics, and the lifecycle of the data. In this way, data governance is the business or process side. Where do you govern?

Data Governance 52

Data Governance Data Quality Metadata Cost-Benefit 52

Cloudera

NOVEMBER 22, 2021

In legacy analytical systems such as enterprise data warehouses, the scalability challenges of a system were primarily associated with computational scalability, i.e., the ability of a data platform to handle larger volumes of data in an agile and cost-efficient way. Limited flexibility to use more complex hosting models (e.g.,

Data Processing 89

Data Processing Data Warehouse Enterprise Visualization 89

Jet Global

FEBRUARY 23, 2024

Data mapping is essential for integration, migration, and transformation of different data sets; it allows you to improve your data quality by preventing duplications and redundancies in your data fields. Data mapping helps standardize, visualize, and understand data across different systems and applications.

Data Warehouse 52

Data Warehouse Reporting Data Transformation Sales 52