erwin

AUGUST 7, 2019

A data catalog benefits organizations in a myriad of ways. With the right data catalog tool, organizations can automate enterprise metadata management – including data cataloging, data mapping, data quality and code generation for faster time to value and greater accuracy for data movement and/or deployment projects.

Metadata 90

Metadata Data Governance Data Quality Data Warehouse 90

Ontotext

NOVEMBER 16, 2023

Think of data mesh as an operational mode for organizations with a domain-driven, decentralized data architecture. It’s a combination of implementation, organizational patterns, and a technology-agnostic set of principles. What Is a Data Product and Who Owns Them?

Metadata 52

Metadata Data-driven Data Quality Data Architecture 52

AWS Big Data

NOVEMBER 29, 2023

As part of the Talent Intelligence Platform Eightfold also exposes a data hub where each customer can access their Amazon Redshift-based data warehouse and perform ad hoc queries as well as schedule queries for reporting and data export. Securing customer data is a top priority for Eightfold.

Metadata 103

Metadata Data Warehouse Analytics Data Analytics 103

AWS Big Data

MARCH 10, 2023

They enable transactions on top of data lakes and can simplify data storage, management, ingestion, and processing. These transactional data lakes combine features from both the data lake and the data warehouse. The Data Catalog provides a central location to govern and keep track of the schema and metadata.

Data Lake 103

Data Lake Sales Data Warehouse Snapshot 103

datapine

SEPTEMBER 29, 2022

Today most of a company’s operations and strategic decisions heavily rely on data, so the importance of quality is even higher. And indeed, low-quality data is the leading cause of failure for advanced data and technology initiatives, to the tune of $9.7 2 – Data profiling. 1 – The people.

Data Quality 241

Data Quality Metrics Data-driven Management 241

Octopai

MARCH 24, 2020

Technology that makes Business Intelligence Intelligent. Let’s start with automated tools that foster the seamless interaction of multiple metadata best practices, such as data discovery, data lineage and the use of a business glossary. Automated metadata management is a key component to bringing datasets together.

Metadata 43

Metadata Cost-Benefit Business Intelligence ROI 43

erwin

FEBRUARY 19, 2021

Metadata management is key to wringing all the value possible from data assets. However, most organizations don’t use all the data at their disposal to reach deeper conclusions about how to drive revenue, achieve regulatory compliance or accomplish other strategic objectives. What Is Metadata? Harvest data.

Metadata 110

Metadata Management Data Quality Cost-Benefit 110

AWS Big Data

FEBRUARY 24, 2023

An AWS Glue streaming job is connected to Kinesis Data Streams to process the data using the Iceberg connector. Athena uses the AWS Glue Data Catalog to store and retrieve table metadata for the Amazon S3 data in Iceberg format. To create your data warehouse or data lake, you must catalog this data.

Data Lake 84

Data Lake Metadata Testing Data Warehouse 84

AWS Big Data

JANUARY 31, 2023

We have collected some of the key talks and solutions on data governance, data mesh, and modern data architecture published and presented in AWS re:Invent 2022, and a few data lake solutions built by customers and AWS Partners for easy reference. Aarthi Srinivasan is a Senior Big Data Architect with AWS Lake Formation.

Data Lake 83

Data Lake Data Governance Data Architecture Data Warehouse 83

AWS Big Data

MARCH 25, 2024

Streaming jobs constantly ingest new data to synchronize across systems and can perform enrichment, transformations, joins, and aggregations across windows of time more efficiently. AWS Glue can interact with streaming data services such as Kinesis Data Streams and Amazon MSK for processing and transforming CDC data.

Data Lake 90

Data Lake Unstructured Data Management Modeling 90

Ontotext

MARCH 8, 2023

Gartner predicts that graph technologies will be used in 80% of data and analytics innovations by 2025, up from 10% in 2021. 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. million users.

Enterprise 52

Enterprise Knowledge Discovery Risk Data-driven 52

datapine

MAY 29, 2019

Business intelligence architecture is a term used to describe standards and policies for organizing data with the help of computer-based techniques and technologies that create business intelligence systems used for online data visualization , reporting, and analysis. One of the BI architecture components is data warehousing.

Business Intelligence 196

Business Intelligence Data Warehouse Dashboards Visualization 196

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. Some of the finer points seem amorphous at best.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

IBM Big Data Hub

JANUARY 18, 2023

They defined it as : “ A data lakehouse is a new, open data management architecture that combines the flexibility, cost-efficiency, and scale of data lakes with the data management and ACID transactions of data warehouses, enabling business intelligence (BI) and machine learning (ML) on all data. ”.

Data Lake 52

Data Lake Data Warehouse Data-driven Metadata 52

AWS Big Data

NOVEMBER 15, 2023

It seamlessly consolidates data from various data sources within AWS, including AWS Cost Explorer (and forecasting with Cost Explorer ), AWS Trusted Advisor , and AWS Compute Optimizer. Data providers and consumers are the two fundamental users of a CDH dataset. You might notice that this differs slightly from traditional ETL.

Dashboards 96

Dashboards Analytics Metadata Data Warehouse 96

Ontotext

FEBRUARY 12, 2024

Although the enterprise data landscape is littered with new data technology and offerings, the most pressing problem data teams face today isn’t a lack of technology or skills; it’s not knowing how to create a modern data experience. Examples include a marketing domain, sales domain, customer domain, etc.

IT 64

IT Metadata Data Quality Data Lake 64

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 85

Enterprise Data Warehouse Data Lake Optimization 85

CIO Business Intelligence

DECEMBER 21, 2022

“The number-one issue for our BI team is convincing people that business intelligence will help to make true data-driven decisions,” says Diana Stout, senior business analyst at Schellman, a global cybersecurity assessor based in Tampa, Fl. Or you have a [BI tool] like Domo, which Schellman uses, that can function as a data warehouse.

IT 131

IT Business Intelligence Sales Key Performance Indicator 131

IBM Big Data Hub

MAY 9, 2023

After some impressive advances over the past decade, largely thanks to the techniques of Machine Learning (ML) and Deep Learning , the technology seems to have taken a sudden leap forward. With watsonx.data , businesses can quickly connect to data, get trusted insights and reduce data warehouse costs.

Data Warehouse 106

Data Warehouse Machine Learning Cost-Benefit Metadata 106

Jen Stirrup

MARCH 29, 2023

Despite technological advances, businesses still need help working with data. Data is complex, and companies often need to catch up on what they are trying to achieve. They are also starting to realize – and accept – that data is challenging. This post was kindly supported by SAP.

Metadata 121

Metadata Data Warehouse Data Integration Business Intelligence 121

Alation

JANUARY 17, 2023

The modern data stack is a combination of various software tools used to collect, process, and store data on a well-integrated cloud-based data platform. It is known to have benefits in handling data due to its robustness, speed, and scalability. A typical modern data stack consists of the following: A data warehouse.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Transformation Data Science 52

AWS Big Data

FEBRUARY 21, 2023

Data warehouses play a vital role in healthcare decision-making and serve as a repository of historical data. A healthcare data warehouse can be a single source of truth for clinical quality control systems. What is a dimensional data model? What is a dimensional data model? What is a data vault?

Data Warehouse 65

Data Warehouse Data Lake Cost-Benefit Metadata 65

AWS Big Data

FEBRUARY 1, 2023

We also used AWS Lambda for data processing. To further optimize and improve the developer velocity for our data consumers, we added Amazon DynamoDB as a metadata store for different data sources landing in the data lake. Clients access this data store with an API’s.

Optimization 52

Optimization Forecasting Data Lake Metadata 52

Alation

FEBRUARY 20, 2020

It’s no longer enough to build the data warehouse. Dave Wells, analyst with the Eckerson Group suggests that realizing the promise of the data warehouse requires a paradigm shift in the way we think about data along with a change in how we access and use it. Building the EDM.

Data Warehouse 52

Data Warehouse Metadata Data Lake Software 52

IBM Big Data Hub

JULY 17, 2023

While they require task-specific labeled data for fine tuning, they also offer clients the best cost performance trade-off for non-generative use cases. offers a Prompt Lab, where users can interact with different prompts using prompt engineering on generative AI models for both zero-shot prompting and few-shot prompting.

Machine Learning 62

Machine Learning Data Warehouse Modeling Cost-Benefit 62

AWS Big Data

OCTOBER 18, 2023

Apache Hive is a distributed, fault-tolerant data warehouse system that enables analytics at a massive scale. Spark SQL is an Apache Spark module for structured data processing. Note: -Your query environment must have the Hive Client tool installed and a connection to your Hive metastore or AWS Glue Data Catalog.

Big Data 81

Big Data Data Processing Interactive Testing 81

AWS Big Data

FEBRUARY 22, 2023

An AWS Glue ETL job, using the Apache Hudi connector, updates the S3 data lake hourly with incremental data. The AWS Glue job can transform the raw data in Amazon S3 to Parquet format, which is optimized for analytic queries. This was an improvement over the weekly report, but still not fast enough to make quicker decisions.

Data Lake 52

Data Lake Dashboards Cost-Benefit Metadata 52

Domino Data Lab

JULY 22, 2019

By virtue of that, if you take those log files of customers interactions, you aggregate them, then you take that aggregated data, run machine learning models on them, you can produce data products that you feed back into your web apps, and then you get this kind of effect in business. You also had the launch of smartphones.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

Octopai

JULY 12, 2020

After all, how do you adjust this month’s operations based on last month’s data if it takes two weeks to finally receive the information you need? This is exactly how Octopai customer, Farm Credit Services of America (FCSA) , felt when their BI team needed to modernize their data warehouse.

Data Warehouse 58

Data Warehouse Data Quality Metadata Risk Management 58

Alation

AUGUST 11, 2021

Across all these strategies, the keys to success are consistent; up-front planning and managing pipelines, alongside attention to governance and metadata are essential. This makes sense: knowing your data and who can access it is a critical first step before any move. Data Governance Supports Smart Cloud Migration.

Data Governance 52

Data Governance Insurance Metadata Strategy 52

AWS Big Data

APRIL 28, 2023

Amazon Redshift is a fast, scalable, secure, and fully managed cloud data warehouse that makes it simple and cost-effective to analyze all your data using standard SQL and your existing ETL (extract, transform, and load), business intelligence (BI), and reporting tools.

Interactive 92

Interactive Metadata Data Warehouse Data-driven 92

IBM Big Data Hub

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 Architecture 59

Data Architecture Data Lake Machine Learning Data Governance 59

CIO Business Intelligence

AUGUST 3, 2023

When global technology company Lenovo started utilizing data analytics, they helped identify a new market niche for its gaming laptops, and powered remote diagnostics so their customers got the most from their servers and other devices. Each of the acquired companies had multiple data sets with different primary keys, says Hepworth. “We

Analytics 98

Analytics Data Lake Metadata Cost-Benefit 98

IBM Big Data Hub

JULY 5, 2023

Fast forward almost 15 years and reality has clearly set in on the trade-offs and compromises this technology entailed. Their fast adoption meant that customers soon lost track of what ended up in the data lake. Data governance remains an unexplored frontier for this technology.

Data Lake 60

Data Lake Metadata Cost-Benefit Data Warehouse 60

Andrew White

JANUARY 11, 2021

So the material is not designed for IT – but spans business and technology. The fill report is here: Leadership Vision for 2021: Data and Analytics. How do you think Technology Business Management plays into this strategy? Where does the Data Architect role fits in the Operational Model ? Product Management.

Data Analytics 52

Data Analytics Analytics Data-driven Finance 52

Jet Global

FEBRUARY 23, 2024

This can involve moving data between different storage systems, databases, or applications. The goal of data migration is to ensure that data is accurately and securely transferred, often to enable better efficiency, scalability, or to adopt new technologies. Data warehouses can be complex, time-consuming, and expensive.

Data Warehouse 52

Data Warehouse Reporting Data Transformation Sales 52

Jet Global

MAY 1, 2023

This is in contrast to traditional BI, which extracts insight from data outside of the app. BI is a set of independent systems (technologies, processes, people, etc.) that gathers data from many sources. These tools prep that data for analysis and then provide reporting on it from a central viewpoint.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52