Ontotext

DECEMBER 15, 2022

Today’s enterprises are increasingly daunted by the realization that more data doesn’t automatically equal deeper knowledge and better business decisions. Obviously, not all of that data is accessible to businesses, but what they can access is still overwhelming. Enter metadata.

Metadata 52

Metadata Unstructured Data Structured Data Enterprise 52

Octopai

FEBRUARY 12, 2020

Like any good puzzle, metadata management comes with a lot of complex variables. That’s why you need to use data dictionary tools, which can help organize your metadata into an archive that can be navigated with ease and from which you can derive good information to power informed decision-making. Why Have a Data Dictionary? #1

Metadata 54

Metadata Enterprise Management Data Warehouse 54

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

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

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 70

Data Warehouse Metadata Interactive Dashboards 70

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

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

Octopai

NOVEMBER 13, 2022

The modern data stack is a data management system built out of cloud-based data systems. A given modern data stack will usually include components for data ingestion from your data sources, data transformation, data storage, data analysis and reporting.

Enterprise 77

Enterprise Data Warehouse Reporting Metadata 77

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

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

Jen Stirrup

MARCH 29, 2023

Put together, these factors help to provide the company with a competitive advantage since better data – and better use of data – leads to better strategies. Data as a product as well as a foundation The data foundation is critical for all types of reporting and analytics.

Metadata 120

Metadata Data Warehouse Data Integration Business Intelligence 120

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 59

Data-driven Enterprise Data Governance Data Lake 59

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. This is one of the biggest hurdles with the data vault approach. What is a dimensional data model?

Data Warehouse 65

Data Warehouse Data Lake Cost-Benefit Modeling 65

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

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. Other senior positions may require an MBA, but there are plenty of BI jobs that require only an undergraduate degree.

Business Intelligence 126

Business Intelligence Data-driven Statistics Data Warehouse 126

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 79

Risk Modeling Management Metadata 79

AWS Big Data

NOVEMBER 29, 2023

In 2013, Amazon Web Services revolutionized the data warehousing industry by launching Amazon Redshift , the first fully-managed, petabyte-scale, enterprise-grade cloud data warehouse. Amazon Redshift made it simple and cost-effective to efficiently analyze large volumes of data using existing business intelligence tools.

Data Warehouse 103

Data Warehouse Data Lake Analytics Machine Learning 103

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 72

Analytics Data Warehouse Data Lake Metadata 72

AWS Big Data

MARCH 26, 2024

Without C360, businesses face missed opportunities, inaccurate reports, and disjointed customer experiences, leading to customer churn. 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.

Data Strategy 70

Data Strategy Strategy Data Warehouse Prescriptive Analytics 70

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.

Management 97

Management Data Warehouse Metrics Dashboards 97

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

Cloudera

DECEMBER 10, 2020

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. Data warehouses have been broadly adopted to provide timely reports and valuable insights.

Data Warehouse 98

Data Warehouse Metadata Cost-Benefit Optimization 98

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

JANUARY 24, 2023

AWS Lake Formation helps with enterprise data governance and is important for a data mesh architecture. It works with the AWS Glue Data Catalog to enforce data access and governance. This solution only replicates metadata in the Data Catalog, not the actual underlying data.

Data Architecture 67

Data Architecture Metadata Data Lake Snapshot 67

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 103

Metadata Data Lake Publishing Data Governance 103

Alation

DECEMBER 15, 2022

December 2012: Alation forms and goes to work creating the first enterprise data catalog. Later, in its inaugural report on data catalogs, Forrester Research recognizes that “Alation started the MLDC trend.”. May 2016: Alation named a Gartner Cool Vendor in their Data Integration and Data Quality, 2016 report.

Metadata 52

Metadata Data Governance Data Quality Marketing 52

Octopai

MAY 18, 2020

Finally, the accounting close is completed and the data is loaded to the data warehouse from which you generate the reports. But wait – there’s a problem: Two of the reports that should match are off by north of $260,000. For a large report in a complex data environment, this process can take weeks.

Metadata 52

Metadata Reporting Business Intelligence Data Warehouse 52

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. Data can be organized into three different zones, as shown in the following figure.

Data Lake 105

Data Lake Sales Data Warehouse Snapshot 105

Octopai

OCTOBER 20, 2021

Octopai, the leader in automated data lineage, data catalog and data discovery, announced today its support and analysis of Amazon Redshift, one of the fastest and most widely used cloud data warehouses. Octopai saves time and resources during the process of migration from on-prem/legacy systems to Amazon Redshift.

Metadata 52

Metadata Data Warehouse Enterprise Business Intelligence 52

Cloudera

NOVEMBER 12, 2020

At these times, they run business growth reports, shareholder reports, and financial reports for their earnings calls, to name a few examples. Cloud deployments for suitable workloads gives you the agility to keep pace with rapidly changing business and data needs.

Data Warehouse 103

Data Warehouse Reporting Risk Cost-Benefit 103

Octopai

NOVEMBER 28, 2019

A better approach is to leave the data sources alone and bring summarized versions of each into a data warehouse. When designed and implemented properly, a data warehouse standardizes data structures from disparate sources to enable apples-to-apples reporting. How Data Lineage Works.

Visualization 54

Visualization Metadata Data Warehouse Reporting 54

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

Octopai

JANUARY 8, 2020

You can’t do this easily without automated data lineage tools. Octopai’s metadata discovery and management suite provides visualization tools that empower you to see and report everything about sensitive customer data. Octopai's Automated Metadata Management Platform can make CCPA compliance a breeze.

Metadata 54

Metadata Key Performance Indicator OLAP Forecasting 54

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

Octopai

MAY 5, 2020

They collected insights from 293 business and IT professionals across a wide range of industries, shining light on why automation metadata operations and the business glossary are priorities for organizations today. Use Case #2: Daily Data Operations. Another BI challenge comes from everyday metadata management operations.

Metadata 52

Metadata Reporting Data Warehouse Management 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 93

Interactive Metadata Data Warehouse Data-driven 93