CIO Business Intelligence

OCTOBER 13, 2023

Data architects are frequently part of a data science team and tasked with leading data system projects. They often report to data infrastructure and data science leads. Application data architect: The application data architect designs and implements data models for specific software applications.

Data Architecture 132

Data Architecture Data Warehouse Statistics Visualization 132

erwin

JUNE 26, 2020

Given the value this sort of data-driven insight can provide, the reason organizations need a data catalog should become clearer. It’s no surprise that most organizations’ data is often fragmented and siloed across numerous sources (e.g., Three Types of Metadata in a Data Catalog. Technical Metadata.

Metadata 132

Metadata Cost-Benefit Measurement Data-driven 132

DataKitchen

AUGUST 3, 2021

The past decades of enterprise data platform architectures can be summarized in 69 words. First-generation – expensive, proprietary enterprise data warehouse and business intelligence platforms maintained by a specialized team drowning in technical debt. Easy to report problems and receive updates on fixes.

Data Architecture 246

Data Architecture Data Lake Cost-Benefit Data Warehouse 246

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. How to scale AL and ML with built-in governance A fit-for-purpose data store built on an open lakehouse architecture allows you to scale AI and ML while providing built-in governance tools.

Risk 76

Risk Modeling Management Metadata 76

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

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 72

Analytics Data Warehouse Data Lake Metadata 72

AWS Big Data

MARCH 10, 2023

However, as data processing at scale solutions grow, organizations need to build more and more features on top of their data lakes. They enable transactions on top of data lakes and can simplify data storage, management, ingestion, and processing. The Iceberg table is synced with the AWS Glue Data Catalog.

Data Lake 105

Data Lake Sales Data Warehouse Snapshot 105

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

MARCH 24, 2020

Business Intelligence has a lot depending on it. 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? So, what is BI Intelligence you ask? Business Glossary.

Metadata 43

Metadata Cost-Benefit Business Intelligence ROI 43

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

AWS Big Data

MARCH 29, 2024

However, to analyze trends over time, aggregate from different dimensions, and share insights across the organization, a purpose-built business intelligence (BI) tool like Amazon QuickSight may be more effective for your business. With these insights, teams have the visibility to make data integration pipelines more efficient.

Metrics 108

Metrics Visualization Dashboards Interactive 108

IBM Big Data Hub

JANUARY 5, 2023

The right data architecture can help your organization improve data quality because it provides the framework that determines how data is collected, transported, stored, secured, used and shared for business intelligence and data science use cases.

Data Quality 52

Data Quality Data Architecture Strategy Data Lake 52

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.

Metadata 52

Metadata Data Warehouse Enterprise Business Intelligence 52

datapine

MAY 29, 2019

BI architecture has emerged to meet those requirements, with data warehousing as the backbone of these processes. One of the BI architecture components is data warehousing. What Is Data Warehousing And Business Intelligence? BI Architecture Framework In Modern Business. Data integration. Data storage.

Business Intelligence 196

Business Intelligence Data Warehouse Dashboards Visualization 196

Octopai

JUNE 15, 2020

Business intelligence databases are dynamic repositories that must often be adjusted based on organizational and or regulatory requirements. To make changes to a system, report, or process, BI developers must first perform impact analysis in order to gauge the potential impact of making such a change on the rest of the environment.

Insurance 52

Insurance Metadata Business Intelligence Data Warehouse 52

Octopai

DECEMBER 10, 2019

Well, scoot over Templeton, because it’s also going to be the year of the Automated Business Glossary for business intelligence and data governance teams everywhere. Automated Business Glossary Tools Streamline Processes. Check out our eBook on Automated Business Glossaries to learn more.

Metadata 53

Metadata Data Warehouse Reporting Business Intelligence 53

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 105

Metadata Data Warehouse Analytics Data Analytics 105

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

CIO Business Intelligence

NOVEMBER 22, 2022

External data sharing gets strategic Data sharing between business partners is becoming far easier and much more cooperative, observes Mike Bechtel, chief futurist at business advisory firm Deloitte Consulting. The fabric, especially at the active metadata level, is important, Saibene notes.

Data Strategy 145

Data Strategy Strategy Enterprise Consulting 145

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. Meaningful business context. Improved trust and confidence in data.

Metadata 52

Metadata Data Quality Data-driven Data Governance 52

FineReport

NOVEMBER 17, 2021

It was an American interactive data visualization software company of business intelligence. Tableau : There are specialized modules to manage metadata. FineReport: When organizing data management, we may face data source replacement. In SQL, the data source table name needs to be changed. FineReport.

KPI 52

KPI Dashboards Metadata Data Warehouse 52

CIO Business Intelligence

SEPTEMBER 6, 2022

When Steve Pimblett joined The Very Group in October 2020 as chief data officer, reporting to the conglomerate’s CIO, his task was to help the enterprise uncover value in its rich data heritage. As a result, Pimblett now runs the organization’s data warehouse, analytics, and business intelligence.

IT 98

IT Forecasting Data Lake Enterprise 98

Octopai

JUNE 1, 2020

Let’s look at how these new requirements have changed the data landscape and how automated data mapping can give your company an advantage. Value of Data Mapping. If your company is merging with another or combining departments, data mapping allows for accurate data integration.

Metadata 52

Metadata Data Warehouse Data Integration Finance 52

Jet Global

JULY 2, 2019

The sheer scale of data being captured by the modern enterprise has necessitated a monumental shift in how that data is stored. From the humble database through to data warehouses , data stores have grown both in scale and complexity to keep pace with the businesses they serve, and the data analysis now required to remain competitive.

Data Lake 73

Data Lake Data Warehouse Big Data Machine Learning 73

FineReport

MAY 6, 2020

Manajemen data: ETL (Extract, Transform, Load), pengelolaan data, management responsibility, metadata. Analisis big data: pembelajaran konsep data tidak terstruktur. Berikut adalah pernyataan dan fungsi yang perlu diketahui seorang data analyst. Data Warehouse. Skill Data Mining.

Data mining 98

Data mining Data Warehouse Machine Learning Big Data 98

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. In the MDM tool, the team should document references to the MDM policy and metadata information from the data catalog.

Management 52

Management Data Quality Metadata Testing 52

Peter James Thomas

AUGUST 18, 2018

That was the Science, here comes the Technology… A Brief Hydrology of Data Lakes. Next, rather than just being the province of Data Scientists, there were moves to use Data Lakes to support general Data Discovery and even business Reporting and Analytics as well. In Closing.

Data Lake 63

Data Lake Data Warehouse Data mining Statistics 63

Alation

JANUARY 26, 2023

Lack of data governance can summon a whole range of problems, including: Lack of consistency For data to be useful, it should be consistent across all areas. A field might not be entered in the same way across different departments, which makes the data difficult to find and affects the accuracy of business intelligence (BI).

Data Governance 52

Data Governance Strategy Data Quality Marketing 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. Data quality details signal to users whether data can be trusted or used. In Summary.

Data Governance 59

Data Governance Risk Data Quality Dashboards 59

CIO Business Intelligence

DECEMBER 21, 2022

Every day, organizations of every description are deluged with data from a variety of sources, and attempting to make sense of it all can be overwhelming. So a strong business intelligence (BI) strategy can help organize the flow and ensure business users have access to actionable business insights. “By

IT 131

IT Business Intelligence Sales Key Performance Indicator 131

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

DataKitchen

SEPTEMBER 21, 2023

Bridging the Gap: How ‘Data in Place’ and ‘Data in Use’ Define Complete Data Observability In a world where 97% of data engineers report burnout and crisis mode seems to be the default setting for data teams, a Zen-like calm feels like an unattainable dream. What is Data in Use?

Testing 169

Testing Data Quality Predictive Modeling Metrics 169

Cloudera

SEPTEMBER 9, 2018

We are proud to announce the general availability of Cloudera Altus Data Warehouse , the only cloud data warehousing service that brings the warehouse to the data. Modern data warehousing for the cloud. Cloudera Altus Data Warehouse is designed with agile data teams in mind.

Data Warehouse 40

Data Warehouse Metadata Cost-Benefit Reporting 40

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

Alation

JANUARY 17, 2023

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 ingestion/integration services. Data orchestration tools. Business intelligence (BI) platforms. Better Data Culture.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Transformation Data Science 52

IBM Big Data Hub

JANUARY 18, 2023

Data platform architecture has an interesting history. Towards the turn of millennium, enterprises started to realize that the reporting and business intelligence workload required a new solution rather than the transactional applications. This adds an additional ETL step, making the data even more stale.

Data Lake 52

Data Lake Data Warehouse Data-driven Metadata 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. 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