Cloudera

SEPTEMBER 24, 2020

Some of the most powerful results come from combining complementary superpowers, and the “dynamic duo” of Apache Hive LLAP and Apache Impala, both included in Cloudera Data Warehouse , is further evidence of this. Both Impala and Hive can operate at an unprecedented and massive scale, with many petabytes of data.

Data Warehouse 71

Data Warehouse Metadata Interactive Dashboards 71

erwin

JULY 2, 2020

Users discuss how they are putting erwin’s data modeling, enterprise architecture, business process modeling, and data intelligences solutions to work. IT Central Station members using erwin solutions are realizing the benefits of enterprise modeling and data intelligence. For Matthieu G., George H., Roshan H.,

Enterprise 122

Enterprise Modeling Metadata Data Governance 122

erwin

SEPTEMBER 3, 2020

Why should you integrate data governance (DG) and enterprise architecture (EA)? Two of the biggest challenges in creating a successful enterprise architecture initiative are: collecting accurate information on application ecosystems and maintaining the information as application ecosystems change.

Data Governance 144

Data Governance Enterprise Risk Data Lake 144

erwin

DECEMBER 12, 2019

Metadata is an important part of data governance, and as a result, most nascent data governance programs are rife with project plans for assessing and documenting metadata. But in many scenarios, it seems that the underlying driver of metadata collection projects is that it’s just something you do for data governance.

Metadata 52

Metadata Data Governance Digital Transformation Data Quality 52

AWS Big Data

FEBRUARY 29, 2024

Data is your generative AI differentiator, and a successful generative AI implementation depends on a robust data strategy incorporating a comprehensive data governance approach. Data governance is a critical building block across all these approaches, and we see two emerging areas of focus.

Data Governance 91

Data Governance Unstructured Data Metadata Data Lake 91

Ontotext

APRIL 10, 2024

Data ecosystems have become jungles and in spite of all the technology, data teams are struggling to create a modern data experience. Drowning in Data, Thirsting for Context We’ve heard the saying, “Data, data everywhere. ” As more data accumulates, context gets diluted and lost.

Metadata 52

Metadata Data Lake Data Warehouse Data Quality 52

CIO Business Intelligence

OCTOBER 13, 2023

Data architect role Data architects are senior visionaries who translate business requirements into technology requirements and define data standards and principles, often in support of data or digital transformations. Data architects are frequently part of a data science team and tasked with leading data system projects.

Data Architecture 132

Data Architecture Data Warehouse Statistics Visualization 132

AWS Big Data

APRIL 29, 2024

Example permission configuration In a practical application within a company, permissions for tables and fields in the data warehouse are divided based on business departments, isolating sensitive data for different business units. This provides data security and orderly conduct of daily business operations.

Management 92

Management Big Data Metadata Data Warehouse 92

AWS Big Data

APRIL 3, 2024

Businesses are constantly evolving, and data leaders are challenged every day to meet new requirements. For many enterprises and large organizations, it is not feasible to have one processing engine or tool to deal with the various business requirements. Snowflake integrates with AWS Glue Data Catalog to retrieve the snapshot location.

Data Lake 91

Data Lake Snapshot Metadata Data Architecture 91

DataKitchen

AUGUST 3, 2021

The data mesh design pattern breaks giant, monolithic enterprise data architectures into subsystems or domains, each managed by a dedicated team. But first, let’s define the data mesh design pattern. The past decades of enterprise data platform architectures can be summarized in 69 words.

Data Architecture 246

Data Architecture Data Lake Cost-Benefit Data Warehouse 246

Ontotext

AUGUST 22, 2023

The age of Big Data inevitably brought computationally intensive problems to the enterprise. Central to today’s efficient business operations are the activities of data capturing and storage, search, sharing, and data analytics. Get these wrong and chances are your enterprise processes and systems will suffer.

Metadata 52

Metadata Knowledge Discovery Big Data Enterprise 52

Alation

FEBRUARY 13, 2020

In an earlier blog, I defined a data catalog as “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.”.

Metadata 52

Metadata Management Data Lake Data Governance 52

IBM Big Data Hub

JUNE 8, 2022

Implementing the right data strategy spurs innovation and outstanding business outcomes by recognizing data as a critical asset that provides insights for better and more informed decision-making. By taking advantage of data, enterprises can shape business decisions, minimize risk for stakeholders, and gain competitive advantage.

Data-driven 58

Data-driven Enterprise Data Governance Data Lake 58

CIO Business Intelligence

MAY 24, 2022

Just after launching a focused data management platform for retail customers in March, enterprise data management vendor Informatica has now released two more industry-specific versions of its Intelligent Data Management Cloud (IDMC) — one for financial services, and the other for health and life sciences.

Finance 140

Finance Management Metadata Data Quality 140

Ontotext

MAY 2, 2024

Storage-centric approach In the storage-centric approach, people try to address data silos by throwing everything in a data lake or a data warehouse. But, although, this helps somewhat in terms of architecture, soon these data lakes become unwieldy. Another complication was the existing data silos.

Metadata 52

Metadata Data Lake Data-driven Enterprise 52

CIO Business Intelligence

JULY 6, 2023

“Our tier strategy resembles a three-layer cake and each of these layers targets different enterprise customers depending on their needs,” said Karan Batta, vice president of Oracle Cloud Infrastructure (OCI). Oracle is also planning to extend the service to enterprises that have their data and applications in their own data centers.

Strategy 113

Strategy Metadata Enterprise Modeling 113

Cloudera

AUGUST 31, 2021

Cloudera and Accenture demonstrate strength in their relationship with an accelerator called the Smart Data Transition Toolkit for migration of legacy data warehouses into Cloudera Data Platform. Accenture’s Smart Data Transition Toolkit . Are you looking for your data warehouse to support the hybrid multi-cloud?

Data Warehouse 84

Data Warehouse Cost-Benefit Metadata Data-driven 84

Cloudera

DECEMBER 10, 2020

Why worry about costs with cloud-native data warehousing? Have you been burned by the unexpected costs of a cloud data warehouse? If not, before adopting a cloud data warehouse, consider the true costs of a cloud-native data warehouse. These costs impede the adoption of cloud-native data warehouses.

Data Warehouse 98

Data Warehouse Metadata Cost-Benefit Optimization 98

AWS Big Data

JULY 27, 2023

Amazon Redshift is a fully managed, scalable cloud data warehouse that accelerates your time to insights with fast, easy, and secure analytics at scale. Tens of thousands of customers rely on Amazon Redshift to analyze exabytes of data and run complex analytical queries, making it the widely used cloud data warehouse.

Data Warehouse 80

Data Warehouse Analytics Metadata Dashboards 80

Octopai

OCTOBER 3, 2019

If you are part of a large organization, chances are good that you’re up to your eyeballs in data. Not only that, but the data you have is probably from multiple sources, stored in multiple formats, and housed in various file systems, databases, and data warehouses. The answer is to build a data catalog.

Enterprise 41

Enterprise Metadata Data Warehouse Consulting 41

CIO Business Intelligence

JUNE 23, 2022

Cloudera customers run some of the biggest data lakes on earth. These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. On data warehouses and data lakes.

Data Lake 98

Data Lake Data Warehouse Machine Learning Cost-Benefit 98

Timo Elliott

JANUARY 6, 2022

Like the proverbial man looking for his keys under the streetlight , when it comes to enterprise data, if you only look at where the light is already shining, you can end up missing a lot. The data you’ve collected and saved over the years isn’t free. Analyze your metadata. Data sense-making.

IT 133

IT Metadata Data-driven Data Governance 133

AWS Big Data

MARCH 7, 2023

Analytics reference architecture for gaming organizations In this section, we discuss how gaming organizations can use a data hub architecture to address the analytical needs of an enterprise, which requires the same data at multiple levels of granularity and different formats, and is standardized for faster consumption.

Analytics 68

Analytics Data Warehouse Data Lake Metadata 68

Cloudera

JUNE 18, 2022

Cloudera customers run some of the biggest data lakes on earth. These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. On data warehouses and data lakes.

Data Lake 92

Data Lake Data Warehouse Machine Learning Cost-Benefit 92

IBM Big Data Hub

APRIL 28, 2022

Data agility, the ability to store and access your data from wherever makes the most sense, has become a priority for enterprises in an increasingly distributed and complex environment. Consequently, a data fabric self-manages and automates data discovery, governance and consumption, which enables.

Metadata 85

Metadata Data Warehouse Forecasting Predictive Modeling 85

Ontotext

MARCH 18, 2020

According to an article in Harvard Business Review , cross-industry studies show that, on average, big enterprises actively use less than half of their structured data and sometimes about 1% of their unstructured data. Why Enterprise Knowledge Graphs? The third challenge is how to combine data management with analytics.

Enterprise 59

Enterprise B2B Unstructured Data Machine Learning 59

IBM Big Data Hub

OCTOBER 16, 2023

It includes processes that trace and document the origin of data, models and associated metadata and pipelines for audits. Curated foundation models, such as those created by IBM or Microsoft, help enterprises scale and accelerate the use and impact of the most advanced AI capabilities using trusted data.

Risk 76

Risk Modeling Management Metadata 76

CIO Business Intelligence

OCTOBER 26, 2023

This is done by mining complex data using BI software and tools , comparing data to competitors and industry trends, and creating visualizations that communicate findings to others in the organization.

Business Intelligence 126

Business Intelligence Data-driven Statistics Data Warehouse 126

Ontotext

MARCH 8, 2023

Use Case #1: Customer 360 / Enterprise 360 Customer data is typically spread across multiple applications, departments, and regions. Each team and system need to keep diverse sets of data about their customers in order to play their specific role – inadvertently leading to siloed experiences. million users.

Enterprise 52

Enterprise Knowledge Discovery Risk Data-driven 52

AWS Big Data

SEPTEMBER 25, 2023

With Amazon Redshift , you can run a complex mix of workloads on your data warehouse, such as frequent data loads running alongside business-critical dashboard queries and complex transformation jobs. We also see more and more data science and machine learning (ML) workloads. ExampleCorp has multiple Redshift clusters.

Management 91

Management Data Warehouse Metrics Dashboards 91

AWS Big Data

APRIL 19, 2023

Many customers run big data workloads such as extract, transform, and load (ETL) on Apache Hive to create a data warehouse on Hadoop. We split the solution into two primary components: generating Spark job metadata and running the SQL on Amazon EMR. The script generates a metadata JSON file for each step.

Metadata 76

Metadata Testing Data Lake Consulting 76

Cloudera

AUGUST 30, 2018

How do I get to the next level in the data-driven journey fast enough? How do I meet a growing demand for self-serve BI, while not exploding my data warehouse budgets? At Cloudera, we believe a strong partnership and the right technology foundation can put you on the path to data-driven success. Tough decisions.

Enterprise 40

Enterprise Data-driven Digital Transformation Machine Learning 40

erwin

OCTOBER 31, 2019

Data security incidents may be the result of not having a true data governance foundation that makes it possible to understand the context of data – what assets exist and where, the relationship between them and enterprise systems and processes, and how and by what authorized parties data is used. No Hocus Pocus.

Data Governance 105

Data Governance Metadata Risk Data Lake 105

IBM Big Data Hub

DECEMBER 16, 2022

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. For example, data catalogs have evolved to deliver governance capabilities like managing data quality and data privacy and compliance.

Metadata 52

Metadata Data Quality Data-driven Data Governance 52

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

Clarifying what data mesh is and how it works is important, but even more so is starting with the why. Why Organizations Need A Data Mesh The data mesh paradigm aims to address some of the biggest pain points for most organizations. This becomes particularly problematic when dealing with veracity of data.

Metadata 52

Metadata Data-driven Data Quality Data Architecture 52

Alation

FEBRUARY 13, 2020

Data curation is important in today’s world of data sharing and self-service analytics, but I think it is a frequently misused term. When speaking and consulting, I often hear people refer to data in their data lakes and data warehouses as curated data, believing that it is curated because it is stored as shareable data.

Metadata 52

Metadata Data Warehouse Data Lake Data Governance 52