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

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

erwin

SEPTEMBER 3, 2020

Data governance provides time-sensitive, current-state architecture information with a high level of quality. It documents your data assets from end to end for business understanding and clear data lineage with traceability. Automating Data Governance and Enterprise Architecture.

Data Governance 144

Data Governance Enterprise Risk Data Lake 144

AWS Big Data

MARCH 7, 2023

Data lakes are more focused around storing and maintaining all the data in an organization in one place. And unlike data warehouses, which are primarily analytical stores, a data hub is a combination of all types of repositories—analytical, transactional, operational, reference, and data I/O services, along with governance processes.

Analytics 69

Analytics Data Warehouse Data Lake Metadata 69

Octopai

NOVEMBER 28, 2019

The result was a spider web of connections and relationships that were difficult to manage, characterize, document, and maintain. Just import data from source A into destination database B. A better approach is to leave the data sources alone and bring summarized versions of each into a data warehouse.

Visualization 54

Visualization Metadata Data Warehouse Reporting 54

datapine

SEPTEMBER 29, 2022

In this article, we will detail everything which is at stake when we talk about DQM: why it is essential, how to measure data quality, the pillars of good quality management, and some data quality control techniques. But first, let’s define what data quality actually is. 2 – Data profiling. 4 – Data Reporting.

Data Quality 241

Data Quality Metrics Data-driven Management 241

Octopai

DECEMBER 10, 2019

This is a company-wide document that defines all important terms used internally, with customers and with vendors. Those terms include entry data, authorship information and they should be interlinked so anyone who looks at it can gain a full understanding of the processes being described. Benefits of an Automated Business Glossary.

Metadata 53

Metadata Data Warehouse Reporting Business Intelligence 53

Octopai

MARCH 24, 2020

Every time someone from Marketing or Sales or HR needs a report created or modified, or every time there’s a problem with some data in a report that needs to be sorted ASAP – who do you call? Here is an overview of how automated metadata management makes your business intelligence smarter. BI, obviously.

Metadata 43

Metadata Cost-Benefit Business Intelligence ROI 43

Cloudera

DECEMBER 21, 2023

How long would it take you to find the data you need to even begin to come up with a data-driven response? In this scenario, you also have reports that need updating as well. No more searching for tables and columns and digging into cryptic metadata with time consuming trial and error just to find the right data sets.

Optimization 66

Optimization Sales Data Warehouse Measurement 66

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.

Metadata 103

Metadata Data Warehouse Analytics Data Analytics 103

erwin

APRIL 27, 2022

In data warehousing, the data is extracted and transported from production database(s) into a data warehouse for reporting and analysis. Change Data Capture identifies and processes only the data that has changed and stores the changed data in a form so as to be of further use.

Data Governance 52

Data Governance Digital Transformation Metadata Data Warehouse 52

erwin

MAY 2, 2022

One must also capture the vast quantity of metadata around the OLTP business requirements that must be reflected. I’m not proposing that business logic be held in the database, but it needs to be documented in the data model even if it will be implemented in application code. Figure 11: Data normalization. Conclusion.

Modeling 98

Modeling Insurance Cost-Benefit Data Warehouse 98

erwin

JANUARY 11, 2019

Organizations have spent a lot of time and money trying to harmonize data across diverse platforms , including cleansing, uploading metadata, converting code, defining business glossaries, tracking data transformations and so on. Creating a High-Quality Data Pipeline.

Data Governance 40

Data Governance Risk Metadata Management 40

FineReport

NOVEMBER 17, 2021

Also, with already organized Help Documents and user-friendly, good ecosphere, FineReport provides resources to solve problems. Tableau : There are specialized modules to manage metadata. FineReport: When organizing data management, we may face data source replacement. Report and Dashboard. Sounds cool, right?

KPI 52

KPI Dashboards Metadata Data Warehouse 52

Octopai

JUNE 1, 2020

Data Warehousing – For data to have value for your company, it needs to be stored in an accessible location. Correct data mapping facilitates the creation of usable, searchable data warehouses. Manual Metadata Management Hinders Compliance.

Metadata 52

Metadata Data Warehouse Data Integration Finance 52

Alation

DECEMBER 21, 2022

Transactional systems and data warehouses can then use the golden records as the entity’s most current, trusted representation. Data Catalog and Master Data Management. Having good data is crucial to creating golden records. MDM Build Objects. The MDM tool should help with this.

Management 52

Management Data Quality Metadata Testing 52

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

Ontotext

MARCH 8, 2023

Rich metadata and semantic modeling continue to drive the matching of 50K training materials to specific curricula, leading new, data-driven, audience-based marketing efforts that demonstrate how the recommender service is achieving increased engagement and performance from over 2.3 million users.

Enterprise 52

Enterprise Knowledge Discovery Risk Data-driven 52

Alation

SEPTEMBER 7, 2021

With Snowflake, data stewards have a choice to leverage Snowflake’s governance policies. First, stewards are dependent on data warehouse admins to provide information and to create and edit enforcement policies in Snowflake. Operationalize data governance at scale. Two problems arise. In Summary.

Data Governance 59

Data Governance Risk Data Quality Dashboards 59

Ontotext

DECEMBER 15, 2022

But whatever their business goals, in order to turn their invisible data into a valuable asset, they need to understand what they have and to be able to efficiently find what they need. Enter metadata. It enables us to make sense of our data because it tells us what it is and how best to use it. Knowledge (metadata) layer.

Metadata 52

Metadata Unstructured Data Structured Data Enterprise 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. faster than overall IT spending.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

AWS Big Data

MARCH 11, 2024

Amazon Redshift is a fully managed, scalable cloud data warehouse that accelerates your time to insights with fast, straightforward, 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 most widely used cloud data warehouse.

Analytics 67

Analytics Data Warehouse Optimization Metrics 67

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

Jet Global

DECEMBER 1, 2020

Finance teams often work with business intelligence (BI) tools to analyze data, identify trends, pinpoint discrepancies, and build informative, compelling reports for management. Microsoft Excel is a phenomenal tool for ad hoc analysis and reporting.

Finance 78

Finance Data Warehouse OLAP Reporting 78

AWS Big Data

MARCH 1, 2024

One of the bank’s key challenges related to strict cybersecurity requirements is to implement field level encryption for personally identifiable information (PII), Payment Card Industry (PCI), and data that is classified as high privacy risk (HPR). Only users with required permissions are allowed to access data in clear text.

Data Lake 99

Data Lake Data Warehouse Management Risk 99

Sisense

SEPTEMBER 3, 2019

This blog is intended to give an overview of the considerations you’ll want to make as you build your Redshift data warehouse to ensure you are getting the optimal performance. Inversely though, if your cluster is used for production reporting (i.e. So let’s dive in! OLTP vs OLAP. Cluster Performance Configurations.

Data Warehouse 78

Data Warehouse OLAP Statistics Cost-Benefit 78

Cloudera

OCTOBER 7, 2022

dbt allows data teams to produce trusted data sets for reporting, ML modeling, and operational workflows using SQL, with a simple workflow that follows software engineering best practices like modularity, portability, and continuous integration/continuous development (CI/CD). Introduction.

Data Warehouse 79

Data Warehouse Data Transformation Testing Data Lake 79

Cloudera

JANUARY 21, 2021

Does your organization’s success depend on immediate delivery of new reports, applications, or projects? While cloud-native, point-solution data warehouse services may serve your immediate business needs, there are dangers to the corporation as a whole when you do your own IT this way. Do you need faster time to value?

Data Lake 93

Data Lake Data Warehouse IT Analytics 93

IBM Big Data Hub

MAY 9, 2023

is not just for data scientists and developers — business users can also access it via an easy-to-use interface that responds to natural language prompts for different tasks. With watsonx.data , businesses can quickly connect to data, get trusted insights and reduce data warehouse costs. Watsonx.ai

Data Warehouse 109

Data Warehouse Cost-Benefit Machine Learning Modeling 109

IBM Big Data Hub

OCTOBER 12, 2023

Among the tasks necessary for internal and external compliance is the ability to report on the metadata of an AI model. Metadata includes details specific to an AI model such as: The AI model’s creation (when it was created, who created it, etc.) This allows for a high degree of transparency and auditability.

Cost-Benefit 83

Cost-Benefit Metadata Data Governance Modeling 83

Ontotext

OCTOBER 14, 2021

For the purposes of this article, you just need to know the following: A graph is a method of storing and modeling data that uniquely captures the relationships between data. A knowledge graph uses this format to integrate data from different sources while enriching it with metadata that documents collective knowledge about the data.

Reporting 98

Reporting Structured Data Metadata Data Warehouse 98

Cloudera

NOVEMBER 5, 2020

Many organizations struggle to meet growing and variable data warehouse demands. This is exactly what Cloudera Data Platform (CDP) provides to the Cloudera Data Warehouse. CDP is a data platform that is optimized for both business units and central IT. . Cloudera Data Warehouse Security.

Data Lake 70

Data Lake Data Warehouse Metadata Optimization 70

Alation

MAY 24, 2022

generally available on May 24, Alation introduces the Open Data Quality Initiative for the modern data stack, giving customers the freedom to choose the data quality vendor that’s best for them with the added confidence that those tools will integrate seamlessly with Alation’s Data Catalog and Data Governance application.

Data Quality 98

Data Quality Data Governance Metadata Metrics 98

Alation

MARCH 1, 2022

Similarly, analysts gain a clear view of how data is created. It’s useful for ensuring compliance downstream and fixing broken reports when a column is to blame. Airline Reporting Corporation (ARC) sells data products to travel agencies and airlines. Time is money,” said Leonard Kwok, Senior Data Analyst, ARC.

Data Warehouse 52

Data Warehouse Data Lake Risk Data-driven 52

AWS Big Data

JUNE 9, 2023

A modern data architecture enables companies to ingest virtually any type of data through automated pipelines into a data lake, which provides highly durable and cost-effective object storage at petabyte or exabyte scale. Frequent table maintenance needs to be performed to prevent read performance from degrading over time.

Data Lake 113

Data Lake Metadata Optimization Statistics 113

BI-Survey

FEBRUARY 23, 2023

Data knowledge is essential to data and analytics There is a clear understanding that data is an asset to the organization. Almost three quarters of respondents also state that they have recognized the need to invest in ways to access, link and understand metadata. These include tools for metadata management (e.g.,

Metadata 52

Metadata Data-driven Data Strategy Strategy 52

Octopai

JULY 19, 2020

The data dictionary remains a crucial tool for BI teams to organize their metadata. The implementation of automation in data technology has made these tools even more powerful. Here is a brief overview of the state of the business data dictionary in 2020 and some best practices to which all data teams should adhere.

Metadata 56

Metadata Data Warehouse Reporting Enterprise 56