Cloudera

JUNE 29, 2023

To improve the way they model and manage risk, institutions must modernize their data management and data governance practices. Implementing a modern data architecture makes it possible for financial institutions to break down legacy data silos, simplifying data management, governance, and integration — and driving down costs.

Data Architecture 85

Data Architecture Risk Management Risk Management 85

AWS Big Data

OCTOBER 10, 2023

Due to the volume, velocity, and variety of data being ingested in data lakes, it can get challenging to develop and maintain policies and procedures to ensure data governance at scale for your data lake. Data confidentiality and data quality are the two essential themes for data governance.

Data Quality 111

Data Quality Data Governance Data Lake Testing 111

Smart Data Collective

FEBRUARY 23, 2021

To help you identify and resolve these mistakes, we’ve put together this guide on the various big data mistakes that marketers tend to make. Big Data Mistakes You Must Avoid. Here are some common big data mistakes you must avoid to ensure that your campaigns aren’t affected. Ignoring Data Quality.

Big Data 142

Big Data Visualization Data Quality Data-driven 142

AWS Big Data

NOVEMBER 22, 2024

This enables you to extract insights from your data without the complexity of managing infrastructure. dbt has emerged as a leading framework, allowing data teams to transform and manage data pipelines effectively. With dbt, teams can define data quality checks and access controls as part of their transformation workflow.

Data Lake 103

Data Lake Data Warehouse Cost-Benefit Data Transformation 103

CIO Business Intelligence

JANUARY 20, 2023

Truly data-driven companies see significantly better business outcomes than those that aren’t. According to a recent IDC whitepaper , leaders saw on average two and a half times better results than other organizations in many business metrics. Most organizations are trying to solve all three problems together,” Tripathy adds.

Data Lake 135

Data Lake Data-driven Finance Data Architecture 135

AWS Big Data

JANUARY 15, 2025

Need for a data mesh architecture Because entities in the EUROGATE group generate vast amounts of data from various sourcesacross departments, locations, and technologiesthe traditional centralized data architecture struggles to keep up with the demands for real-time insights, agility, and scalability.

IoT 111

IoT Machine Learning Metadata Data-driven 111

DataKitchen

OCTOBER 11, 2021

First, you must understand the existing challenges of the data team, including the data architecture and end-to-end toolchain. Based on business rules, additional data quality tests check the dimensional model after the ETL job completes. A DataOps implementation project consists of three steps.

Testing 154

Testing Metadata Dashboards Statistics 154

AWS Big Data

AUGUST 1, 2024

Migrating to Amazon Redshift offers organizations the potential for improved price-performance, enhanced data processing, faster query response times, and better integration with technologies such as machine learning (ML) and artificial intelligence (AI).

Data Warehouse 115

Data Warehouse KPI Optimization Cost-Benefit 115

AWS Big Data

DECEMBER 4, 2024

While traditional extract, transform, and load (ETL) processes have long been a staple of data integration due to its flexibility, for common use cases such as replication and ingestion, they often prove time-consuming, complex, and less adaptable to the fast-changing demands of modern data architectures.

Data Integration 114

Data Integration Data Lake Statistics Data-driven 114

AWS Big Data

JULY 20, 2023

With data becoming the driving force behind many industries today, having a modern data architecture is pivotal for organizations to be successful. Prior to the creation of the data lake, Orca’s data was distributed among various data silos, each owned by a different team with its own data pipelines and technology stack.

Data Lake 98

Data Lake Analytics Snapshot Data Quality 98

Cloudera

DECEMBER 1, 2022

Full-stack observability is a critical requirement for effective modern data platforms to deliver the agile, flexible, and cost-effective environment organizations are looking for. RI is a global leader in the design and deployment of large-scale, production-level modern data platforms for the world’s largest enterprises.

Data Quality 84

Data Quality Metrics Data Lake Statistics 84

CIO Business Intelligence

NOVEMBER 29, 2022

A sea of complexity For years, data ecosystems have gotten more complex due to discrete (and not necessarily strategic) data-platform decisions aimed at addressing new projects, use cases, or initiatives. Layering technology on the overall data architecture introduces more complexity. Data and cloud strategy must align.

Data Architecture 111

Data Architecture Data Integration IoT Data-driven 111

CIO Business Intelligence

JUNE 9, 2023

A few years ago, Gartner found that “organizations estimate the average cost of poor data quality at $12.8 million per year.’” Beyond lost revenue, data quality issues can also result in wasted resources and a damaged reputation. Data management’s ROI Customers often ask me how to “make the case” for data management.

Strategy 116

Strategy Management Key Performance Indicator Cost-Benefit 116

Cloudera

JULY 20, 2021

Invest in maturing and improving your enterprise business metrics and metadata repositories, a multitiered data architecture, continuously improving data quality, and managing data acquisitions. Then back this up by embedding compliance and security protocols throughout the insights generation cycle.

Manufacturing 106

Manufacturing Forecasting IoT Insurance 106

AWS Big Data

NOVEMBER 9, 2023

As part of their cloud modernization initiative, they sought to migrate and modernize their legacy data platform. Third-party APIs – These provide analytics and survey data related to ecommerce websites. This could include details like traffic metrics, user behavior, conversion rates, customer feedback, and more.

Data Warehouse 126

Data Warehouse Testing Data Quality Reporting 126

Sisense

SEPTEMBER 3, 2020

Programming and statistics are two fundamental technical skills for data analysts, as well as data wrangling and data visualization. Data analysts in one organization might be called data scientists or statisticians in another. Database design is often an important part of the business analyst role.

Statistics 97

Statistics Metrics Visualization Finance 97

AWS Big Data

MARCH 26, 2024

In 2022, AWS commissioned a study conducted by the American Productivity and Quality Center (APQC) to quantify the Business Value of Customer 360. The following figure shows some of the metrics derived from the study. The AWS modern data architecture shows a way to build a purpose-built, secure, and scalable data platform in the cloud.

Data Strategy 98

Data Strategy Strategy Data Warehouse Prescriptive Analytics 98

IBM Big Data Hub

DECEMBER 4, 2023

This phase of planning also covers projected project milestones and well-defined metrics for the system once it goes live. During configuration, an organization constructs its data architecture and defines user roles. Data quality: Ensure migrated data is clean, correct and current.

Testing 71

Testing Consulting Digital Transformation Cost-Benefit 71

Alation

OCTOBER 12, 2021

The third challenge was around trusting the data. There are inconsistent definitions and inconsistent metrics, and a lack of trust in the data used in the metrics. The fourth challenge was around using the data. There was a real lack of confidence in using the data and the risk of using the wrong data.

Strategy 52

Strategy Enterprise Analytics Data Governance 52

Alation

JANUARY 25, 2022

In a practical sense, a modern data catalog should capture a broad array of metadata that also serves a broader array of consumers. In concrete terms, that includes metadata for a broad array of asset classes, such as BI reports, business metrics, business terms, domains, functional business processes, and more.

Metadata 52

Metadata IT Data-driven Metrics 52

CIO Business Intelligence

FEBRUARY 20, 2023

To earn the Salesforce Data Architect certification , candidates should be able to design and implement data solutions within the Salesforce ecosystem, such as data modelling, data integration and data governance. This credential proves that you can design, build, and implement Service Cloud functionality.

Consulting 87

Consulting B2B Sales Cost-Benefit 87

Andrew White

JANUARY 9, 2022

This is the same for scope, outcomes/metrics, practices, organization/roles, and technology. Check this out: The Foundation of an Effective Data and Analytics Operating Model — Presentation Materials. Most of D&A concerns and activities are done within EA in the Info/Data architecture domain/phases.

Analytics 64

Analytics Measurement Data-driven Modeling 64

CIO Business Intelligence

FEBRUARY 25, 2025

Still, many organizations arent yet ready to fully take advantage of AI because they lack the foundational building blocks around data quality and governance. Most organizations are currently at the data integration, data governance, and data strategy level, so they need to hire the right CIO to advance those areas.

Uncertainty 126

Uncertainty Cost-Benefit Data-driven Marketing 126

AWS Big Data

APRIL 29, 2025

While enabling organization-wide efficiency, the team also applied these principles to the data architecture, making sure that CLEA itself operates frugally. After evaluating various tools, we built a serverless data transformation pipeline using Amazon Athena and dbt. However, our initial data architecture led to challenges.

Data Transformation 54

Data Transformation Cost-Benefit Testing Data Lake 54

DataKitchen

JANUARY 23, 2023

It allows organizations to see how data is being used, where it is coming from, its quality, and how it is being transformed. DataOps Observability includes monitoring and testing the data pipeline, data quality, data testing, and alerting. Are problems with data tests? Which report tab is wrong?

Testing 130

Testing Data Governance Data Quality Data-driven 130