Sisense

JULY 6, 2020

These regulations, ultimately, ensure key business values: data consistency, quality, and trustworthiness. Data architecture creates instructions that guide you through the data collection, integration, and transformation processes, as well as data modeling.

Enterprise 98

Enterprise Management Data Architecture Data-driven 98

Cloudera

MAY 9, 2023

At the same time, telecommunications carriers’ user location data that has been aggregated, anonymized, and processed is converted into data products that are then provided to business customers. We believe these new data analysis capabilities will boost what we can offer to our customers.”

Data Lake 90

Data Lake IoT Data Governance Data Strategy 90

CIO Business Intelligence

SEPTEMBER 14, 2023

What is a data engineer? Data engineers design, build, and optimize systems for data collection, storage, access, and analytics at scale. They create data pipelines that convert raw data into formats usable by data scientists, data-centric applications, and other data consumers.

Analytics 135

Analytics Data Science Unstructured Data Data mining 135

CIO Business Intelligence

MARCH 24, 2023

The Business Application Research Center (BARC) warns that data governance is a highly complex, ongoing program, not a “big bang initiative,” and it runs the risk of participants losing trust and interest over time.

Data Governance 142

Data Governance Management Metadata Data Quality 142

CIO Business Intelligence

AUGUST 9, 2022

What is a data engineer? Data engineers design, build, and optimize systems for data collection, storage, access, and analytics at scale. They create data pipelines used by data scientists, data-centric applications, and other data consumers. Data engineer vs. data architect.

Analytics 131

Analytics Data Science Statistics Unstructured Data 131

CIO Business Intelligence

JANUARY 30, 2024

Only a few enterprises have adopted fully automated ESG data collection and monitoring tools; the majority still depend on unreliable manual practices,” Everest’s Narayanan says. From there, CIOs can determine the most relevant pieces of data and how to source and automate the gathering of that data, IDC’s Cravens says.

Reporting 115

Reporting Data Quality Strategy Data-driven 115

Cloudera

OCTOBER 11, 2022

The takeaway – businesses need control over all their data in order to achieve AI at scale and digital business transformation. The challenge for AI is how to do data in all its complexity – volume, variety, velocity. We believe the best path is with a hybrid data platform for modern data architectures with data anywhere.

Data Science 94

Data Science Snapshot Data Warehouse Metadata 94

Cloudera

APRIL 19, 2023

Data has become an essential driver for new monetization initiatives in the financial services industry. Shifting to a data-driven culture To fully realize the value of their data, financial services firms must create a data-driven culture that prioritizes the use of data in decision-making and innovation.

Data-driven 70

Data-driven Data Architecture Measurement Risk 70

CIO Business Intelligence

MARCH 19, 2025

Integrating ESG into data decision-making CDOs should embed sustainability into data architecture, ensuring that systems are designed to optimize energy efficiency, minimize unnecessary data replication and promote ethical data use.

IT 59

IT Data Governance Data-driven Metrics 59

IBM Big Data Hub

MAY 15, 2024

The remote execution concept unlocks the potential for edge data processing by allowing users to deploy lightweight, containerized ETL/ELT engines directly on edge devices or within edge computing environments. Organizations can harness the full potential of their data while reducing risk and lowering costs.

Cost-Benefit 67

Cost-Benefit Data Integration Data Architecture Manufacturing 67

IBM Big Data Hub

SEPTEMBER 19, 2023

Though you may encounter the terms “data science” and “data analytics” being used interchangeably in conversations or online, they refer to two distinctly different concepts. Meanwhile, data analytics is the act of examining datasets to extract value and find answers to specific questions.

Data Science 76

Data Science Data Analytics Prescriptive Analytics Analytics 76

IBM Big Data Hub

OCTOBER 16, 2023

” Bias, AI and IBM A proper technology mix can be crucial to an effective data and AI governance strategy, with a modern data architecture and trustworthy AI platform being key components. Policy orchestration within a data fabric architecture is an excellent tool that can simplify the complex AI audit processes.

Advertising 68

Advertising Machine Learning Data Architecture Cost-Benefit 68

Sisense

SEPTEMBER 3, 2020

Overall, however, what often characterizes them is a focus on data collection, manipulation, and analysis, using standard formulas and methods, and acting as gatekeepers of an organization’s data. Data analysts might report to a CIO, a Chief Data Officer (CDO), or possibly to a data scientist or business analyst team leader.

Statistics 97

Statistics Metrics Visualization Finance 97

Cloudera

SEPTEMBER 8, 2021

A simplified enterprise data architecture looks something like the figure below. It is unlikely that your organization’s architecture is an exact match, but you can probably recognise and identify many of the logical components. Entire data flows from the edge to AI can be controlled within one platform.

Data Lake 79

Data Lake Enterprise Data-driven Data Strategy 79

AWS Big Data

MARCH 26, 2024

In this post, we discuss how you can use purpose-built AWS services to create an end-to-end data strategy for C360 to unify and govern customer data that address these challenges. We recommend building your data strategy around five pillars of C360, as shown in the following figure.

Data Strategy 78

Data Strategy Strategy Data Warehouse Prescriptive Analytics 78

TDAN

AUGUST 7, 2024

The Internet of Things (IoT) is changing industries by enabling real-time data collection and analysis from many connected devices. IoT applications rely heavily on real-time data streaming to drive insights and actions from smart homes and cities to industrial automation and healthcare.

IoT 52

IoT Internet of Things Data Collection Data Architecture 52

IBM Big Data Hub

FEBRUARY 9, 2023

Realize that a data governance program cannot exist on its own – it must solve business problems and deliver outcomes. Start by identifying business objectives, desired outcomes, key stakeholders, and the data needed to deliver these objectives. Don’t try to do everything at once!

Data Governance 76

Data Governance Business Objectives Data Quality Measurement 76

IBM Big Data Hub

JUNE 8, 2023

Having a well-designed data architecture and fact-based data can help with understanding performance and measuring progress against broad-based operational and ESG goals. Insights generated from this data can help organizations further their ESG programs as well as drive operational efficiency.

Technology 76

Technology Measurement Cost-Benefit Data-driven 76

TDAN

JULY 4, 2023

The O*NET Data Collection Program, which is sponsored by the U.S. Department of Labor, is seeking the input of expert Data Warehousing Specialists. You have the opportunity to participate […]

Data Collection 52

Data Collection Data Architecture Data Warehouse Data Strategy 52

Cloudera

OCTOBER 1, 2022

While the word “data” has been common since the 1940s, managing data’s growth, current use, and regulation is a relatively new frontier. . Governments and enterprises are working hard today to figure out the structures and regulations needed around data collection and use.

Data Governance 75

Data Governance Strategy Enterprise Machine Learning 75

Alation

OCTOBER 12, 2021

Folks can work faster, and with more agility, unearthing insights from their data instantly to stay competitive. Yet the explosion of data collection and volume presents new challenges. Set expectations for usage based on role and data source. Create a blueprint of data architecture to find inconsistent definitions.

Strategy 52

Strategy Enterprise Analytics Data Governance 52

Ontotext

NOVEMBER 16, 2023

Figure 1 Shows the overall idea of a data mesh with the major components: What Is a Data Mesh and How Does It Work? Think of data mesh as an operational mode for organizations with a domain-driven, decentralized data architecture.

Metadata 52

Metadata Data-driven Data Quality Data Architecture 52

Alation

FEBRUARY 13, 2020

Today, we’re announcing that Alation has closed a $50 million Series C funding led by Sapphire Ventures, with participation from new investor Salesforce Ventures and our existing investors Costanoa Ventures, DCVC (Data Collective), Harmony Partners and Icon Ventures.

Enterprise 52

Enterprise Data Lake Machine Learning Data-driven 52

AWS Big Data

NOVEMBER 15, 2023

Furthermore, it fetches essential metadata from BMW Group’s internal system, offering a comprehensive view of the data across various dimensions, such as group, department, product, and applications in the later stages of data transformation. Selman Ay is a Data Architect in the AWS Professional Services team.

Dashboards 106

Dashboards Analytics Metadata Data Warehouse 106

Alation

JULY 7, 2022

In the 2010s, the growing scope of the data landscape gave rise to a new profession: the data scientist. This new role, combined with the creation of data lakes and the increasing use of cloud services, created new employment opportunities in data analytics, data architecture, and data management.

Metadata 52

Metadata Data-driven Insurance Statistics 52

Alation

APRIL 25, 2023

More specifically, it describes the process of creating, administering, and adapting a comprehensive plan for how an organization’s data will be managed. In this way, data governance has implications for a wide range of data management disciplines, including data architecture, quality, security, metadata, and more.

Data Governance 52

Data Governance Marketing Machine Learning Sales 52

Alation

APRIL 25, 2023

More specifically, it describes the process of creating, administering, and adapting a comprehensive plan for how an organization’s data will be managed. In this way, data governance has implications for a wide range of data management disciplines, including data architecture, quality, security, metadata, and more.

Data Governance 40

Data Governance Marketing Machine Learning Sales 40

TDAN

OCTOBER 1, 2019

IoT has a lot more to offer than merely establishing connections between systems and devices. We are in the digital age that Hollywood once fancied with sophisticated connected devices and technologies surfacing day after day. IoT is paving ways for new services and products, which were just a figment of our imagination up until a […].

IoT 40

IoT Internet of Things Technology Data Architecture 40

Andrew White

JANUARY 9, 2022

Most of D&A concerns and activities are done within EA in the Info/Data architecture domain/phases. I would think a key importance would be how you generate and what data points are used to analyze especially if it is manually retrieved. They can all help you at any time depending not the context.

Analytics 64

Analytics Measurement Data-driven Modeling 64

IBM Big Data Hub

MARCH 7, 2023

At Innocens BV, the belief is that earlier identification of sepsis-related events in newborns is possible, especially given the vast amount of data points collected from the moment a baby is born. Years’ worth of aggregated data in the NICU could help lead us to a solution.

Risk 52

Risk Technology Informatics Predictive Modeling 52

Jet Global

MAY 1, 2023

Let’s just give our customers access to the data. You’ve settled for becoming a data collection tool rather than adding value to your product. While data exports may satisfy a portion of your customers, there will be many who simply want reports and insights that are available “out of the box.”

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52

DataKitchen

JANUARY 23, 2023

Like an apartment blueprint, Data lineage provides a written document that is only marginally useful during a crisis. This is especially true in the case of the one-to-many, producer-to-consumer relationships we have on our data architecture. Are problems with data tests? Which report tab is wrong? When did it last run?

Testing 130

Testing Data Governance Data Quality Data-driven 130