DataKitchen

AUGUST 3, 2021

First-generation – expensive, proprietary enterprise data warehouse and business intelligence platforms maintained by a specialized team drowning in technical debt. Second-generation – gigantic, complex data lake maintained by a specialized team drowning in technical debt. See the pattern?

Data Architecture 246

Data Architecture Data Lake Cost-Benefit Data Warehouse 246

CIO Business Intelligence

MARCH 9, 2022

Applying artificial intelligence (AI) to data analytics for deeper, better insights and automation is a growing enterprise IT priority. But the data repository options that have been around for a while tend to fall short in their ability to serve as the foundation for big data analytics powered by AI.

Data Lake 102

Data Lake Unstructured Data Data Warehouse Data Quality 102

Alation

MARCH 21, 2023

Why is data analytics important for travel organizations? With data analytics , travel organizations can gain real-time insights about customers to make strategic decisions and improve their travel experience. They may also suffer from data duplication, which undermines their analytics models.

Data Analytics 52

Data Analytics Analytics Data-driven Big Data 52

AWS Big Data

OCTOBER 4, 2023

An Amazon DataZone domain contains an associated business data catalog for search and discovery, a set of metadata definitions to decorate the data assets that are used for discovery purposes, and data projects with integrated analytics and ML tools for users and groups to consume and publish data assets.

Metadata 102

Metadata Data Lake Publishing Data Governance 102

CIO Business Intelligence

NOVEMBER 4, 2022

We’ll work with those scientists and actually build the computer models and go run it, and it can be anything from sub-physical particle imaging to protein folding,” he says. “In In other cases, it’s more of a standard computational requirement and we help them provide the data in the right formats.

Data Lake 109

Data Lake IT Experimentation Data-driven 109

AWS Big Data

MARCH 26, 2024

Profile aggregation – When you’ve uniquely identified a customer, you can build applications in Managed Service for Apache Flink to consolidate all their metadata, from name to interaction history. Then, you transform this data into a concise format. Let’s find out what role each of these components play in the context of C360.

Data Strategy 70

Data Strategy Strategy Data Warehouse Prescriptive Analytics 70

AWS Big Data

DECEMBER 18, 2023

Amazon Redshift empowers users to extract powerful insights by securely and cost-effectively analyzing data across data warehouses, operational databases, data lakes, third-party data stores, and streaming sources using zero-ETL approaches.

Data Warehouse 100

Data Warehouse Machine Learning Data-driven Data Lake 100

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 92

Data Lake Unstructured Data Management Modeling 92

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 81

Management Metadata Data Architecture Data Lake 81

IBM Big Data Hub

MAY 9, 2023

The answer is that generative AI leverages recent advances in foundation models. Unlike traditional ML, where each new use case requires a new model to be designed and built using specific data, foundation models are trained on large amounts of unlabeled data, which can then be adapted to new scenarios and business applications.

Data Warehouse 107

Data Warehouse Machine Learning Cost-Benefit Metadata 107

Cloudera

APRIL 22, 2021

Today’s enterprise data analytics teams are constantly looking to get the best out of their platforms. Storage plays one of the most important roles in the data platforms strategy, it provides the basis for all compute engines and applications to be built on top of it. Metadata in cluster is disjoint across components.

Data Lake 100

Data Lake Cost-Benefit Testing Metadata 100

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 78

Cost-Benefit Metadata Data Governance Modeling 78

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.

Data Lake 91

Data Lake Data Warehouse Data-driven B2B 91

Ontotext

FEBRUARY 12, 2024

Transferring ownership of data/datasets to domain-specific units that possess a deeper understanding of rules around the data empowers teams, improves data quality and trust, and greatly accelerates the building of data models and analytics. However, data mesh is not about introducing new technologies.

Data-driven 59

Data-driven Data Lake Data Quality Business Objectives 59

IBM Big Data Hub

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. It uses knowledge graphs, semantics and AI/ML technology to discover patterns in various types of metadata.

Data Architecture 60

Data Architecture Data Lake Machine Learning Data Governance 60

AWS Big Data

JULY 14, 2023

The FinAuto team built AWS Cloud Development Kit (AWS CDK), AWS CloudFormation , and API tools to maintain a metadata store that ingests from domain owner catalogs into the global catalog. This global catalog captures new or updated partitions from the data producer AWS Glue Data Catalogs.

Finance 86

Finance Metadata Big Data Recreation/Entertainment 86

AWS Big Data

MAY 1, 2024

Excel-based data utilization Microsoft Excel is available on almost everyone’s PC in the company, and it helps lower the hurdles when starting to utilize data. However, Excel is mainly designed for spreadsheets; it’s not designed for large-scale data analytics and automation.

Dashboards 113

Dashboards Data-driven Publishing Cost-Benefit 113

AWS Big Data

FEBRUARY 21, 2023

Data warehouses are mostly built using the dimensional model approach, which has consistently met business needs. Additionally, scalability of the dimensional model is complex and poses a high risk of data integrity issues. What is a dimensional data model?

Data Warehouse 67

Data Warehouse Data Lake Cost-Benefit Modeling 67

DataKitchen

OCTOBER 11, 2021

The biggest challenge is broken data pipelines due to highly manual processes. Figure 1 shows a manually executed data analytics pipeline. First, a business analyst consolidates data from some public websites, an SFTP server and some downloaded email attachments, all into Excel. Monitoring Job Metadata.

Testing 152

Testing Metadata Dashboards Statistics 152

Ontotext

FEBRUARY 26, 2024

However, it still requires more effort than building a single-purpose graph, like a labeled property graph (LPG), where you can whiteboard your graph model in an hour. Firstly, on the data maturity spectrum, the vast majority of organizations I’ve spoken with are stuck in the information stage. RDF vs LPG?

Technology 52

Technology Cost-Benefit Data-driven Metadata 52

IBM Big Data Hub

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 Architecture Strategy Data Lake 52

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. After all, Alex may not be aware of all the data available to her.

Metadata 52

Metadata Data Quality Data-driven Data Governance 52

Andrew White

DECEMBER 9, 2019

The client had recently engaged with a well-known consulting company that had recommended a large data catalog effort to collect all enterprise metadata to help identify all data and business issues. With this, the recommendation was the formation of a large enterprise data governance board with CEO sponsorship.

Analytics 66

Analytics Data Lake Data Governance Metadata 66

Alation

JULY 19, 2022

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. Obstacles, such as user roles, permissions, and approval request prevent speedy data access.

Metadata 59

Metadata Data Quality Statistics Data Science 59

Alation

JULY 7, 2022

In 2013 I joined American Family Insurance as a metadata analyst. I had always been fascinated by how people find, organize, and access information, so a metadata management role after school was a natural choice. The use cases for metadata are boundless, offering opportunities for innovation in every sector.

Metadata 52

Metadata Data-driven Insurance Statistics 52

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. Governance of Data Drift.

Metadata 59

Metadata Data Governance Modeling Data-driven 59

IBM Big Data Hub

MARCH 14, 2024

The solution: IBM databases on AWS To solve for these challenges, IBM’s portfolio of SaaS database solutions on Amazon Web Services (AWS), enables enterprises to scale applications, analytics and AI across the hybrid cloud landscape.

Cost-Benefit 77

Cost-Benefit Metadata Optimization Management 77

CIO Business Intelligence

SEPTEMBER 6, 2022

“‘It’ being everything from how they collect and measure data, to how they understand it and their own glossary. It was very fragmented, and I brought it together into a hub-and-spoke model.”. The new model enables Very to design once and deploy everywhere, while maintaining a product focus. Where do we store it?

IT 82

IT Forecasting Data Lake Enterprise 82

AWS Big Data

JUNE 6, 2023

Unless, of course, the rest of their data also resides in the Google Cloud. In this post we showcase how we used AWS Glue to move siloed digital analytics data, with inconsistent arrival times, to AWS S3 (our Data Lake) and our central data warehouse (DWH), Snowflake.

Analytics 55

Analytics Data Lake Testing Optimization 55

AWS Big Data

JANUARY 22, 2024

Data as a product Treating data as a product entails three key components: the data itself, the metadata, and the associated code and infrastructure. In this approach, teams responsible for generating data are referred to as producers. All other teams can be data producers or data consumers.

Data-driven 87

Data-driven Advertising Metadata Data Architecture 87

Cloudera

MAY 12, 2021

We welcome organizations that have built and deployed use cases for enterprise-scale machine learning and have industrialized AI to automate, secure, and optimize data-driven decision-making and/or applications to enter this category. HYBRID & MULTI-CLOUD INNOVATION.

Digital Transformation 68

Digital Transformation Machine Learning Optimization Data Lake 68

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

AUGUST 4, 2021

And if data security tops IT concerns, data governance should be their second priority. Not only is it critical to protect data, but data governance is also the foundation for data-driven businesses and maximizing value from data analytics.

Data Governance 85

Data Governance Metadata Data-driven Enterprise 85

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. Note: Delivery of data, analytics solutions and the sustainment of technology, data and services is a question. Governance. Architecture.

Data Analytics 52

Data Analytics Analytics Data-driven Finance 52

Andrew White

MARCH 22, 2019

to weave together the governance and management of master data, application data, and less-widely shared data, and just enough enterprise metadata management. Your Future Requires You to Define Your Real Master Data. This ties into the failure of data governance and MDM (see first item in this list).

Analytics 68

Analytics Metadata Data Governance Management 68

Cloudera

JANUARY 22, 2019

Forrester describes Big Data Fabric as, “A unified, trusted, and comprehensive view of business data produced by orchestrating data sources automatically, intelligently, and securely, then preparing and processing them in big data platforms such as Hadoop and Apache Spark, data lakes, in-memory, and NoSQL.”.

Big Data 44

Big Data Data Lake Internet of Things Enterprise 44

Cloudera

AUGUST 21, 2020

Over time, additional use cases and functions expanded from original EDW and Data Lake related functions to support increasing demands from the business. More sources, data, and functionality were added to these platforms, expanding their value but adding to the complexity, such as: Streaming data ingestion. .

Cost-Benefit 74

Cost-Benefit Big Data ROI Risk 74