CIO Business Intelligence

MARCH 19, 2025

As regulatory scrutiny, investor expectations, and consumer demand for environmental, social and governance (ESG) accountability intensify, organizations must leverage data to drive their sustainability initiatives. However, embedding ESG into an enterprise data strategy doesnt have to start as a C-suite directive.

IT 59

IT Data Governance Data-driven Metrics 59

DataKitchen

DECEMBER 20, 2020

Data-driven companies sense change through data analytics. Companies turn to their data organization to provide the analytics that stimulates creative problem-solving. The speed at which the data team responds to these requests is critical. The agility of analytics directly relates to data analytics workflows.

Data-driven 147

Data-driven Manufacturing Data Architecture Data Analytics 147

CIO Business Intelligence

NOVEMBER 29, 2022

By George Trujillo, Principal Data Strategist, DataStax Innovation is driven by the ease and agility of working with data. Increasing ROI for the business requires a strategic understanding of — and the ability to clearly identify — where and how organizations win with data.

Data Architecture 111

Data Architecture Data Integration IoT Data-driven 111

IBM Big Data Hub

JULY 13, 2023

When we talk about data integrity, we’re referring to the overarching completeness, accuracy, consistency, accessibility, and security of an organization’s data. Together, these factors determine the reliability of the organization’s data. In short, yes.

Data Quality 63

Data Quality Data Integration Metadata Cost-Benefit 63

IBM Big Data Hub

JANUARY 5, 2023

Poor data quality is one of the top barriers faced by organizations aspiring to be more data-driven. Ill-timed business decisions and misinformed business processes, missed revenue opportunities, failed business initiatives and complex data systems can all stem from data quality issues.

Data Architecture 52

Data Architecture Data Quality Strategy Data Lake 52

CIO Business Intelligence

JUNE 16, 2022

By George Trujillo, Principal Data Strategist, DataStax. Any enterprise data management strategy has to begin with addressing the 800-pound gorilla in the corner: the “innovation gap” that exists between IT and business teams. This scarcity of quality data might feel akin to dying of thirst in the middle of the ocean.

IT 135

IT Experimentation IoT Data-driven 135

erwin

JANUARY 9, 2020

Enterprises are trying to manage data chaos. They also face increasing regulatory pressure because of global data regulations , such as the European Union’s General Data Protection Regulation (GDPR) and the new California Consumer Privacy Act (CCPA), that went into effect last week on Jan. GDPR: Key Differences.

Data Governance 144

Data Governance Modeling Metadata Unstructured Data 144

IBM Big Data Hub

JANUARY 17, 2023

Due to the convergence of events in the data analytics and AI landscape, many organizations are at an inflection point. Furthermore, a global effort to create new data privacy laws, and the increased attention on biases in AI models, has resulted in convoluted business processes for getting data to users. Data governance.

Data-driven 56

Data-driven Enterprise Data Governance Data Science 56

Data Virtualization

SEPTEMBER 21, 2023

Reading Time: 2 minutes In the ever-evolving landscape of data management, one concept has been garnering the attention of companies and challenging traditional centralized data architectures. This concept is known as “data mesh,” and it has the potential to revolutionize the way organizations handle.

Management 105

Management Data Architecture Data Integration Data-driven 105

Data Virtualization

OCTOBER 27, 2023

Kafka is used when real-time data streaming and event-driven architectures with scalable data processing are essential.

Data Integration 52

Data Integration Data-driven Data Processing Management 52

AWS Big Data

NOVEMBER 28, 2023

As customers become more data driven and use data as a source of competitive advantage, they want to easily run analytics on their data to better understand their core business drivers to grow sales, reduce costs, and optimize their businesses. ETL is the process data engineers use to combine data from different sources.

Data Warehouse 120

Data Warehouse Data-driven Machine Learning B2B 120

AWS Big Data

APRIL 3, 2024

Businesses are constantly evolving, and data leaders are challenged every day to meet new requirements. Customers are using AWS and Snowflake to develop purpose-built data architectures that provide the performance required for modern analytics and artificial intelligence (AI) use cases.

Data Lake 121

Data Lake Snapshot Metadata Data Architecture 121

BI-Survey

AUGUST 21, 2020

Data warehousing is getting on in years. Concepts and architectures have been applied more or less unchanged since the 1990s. However, data warehousing and BI applications are only considered moderately successful. But what are the right measures to make the data warehouse and BI fit for the future?

Data Warehouse 98

Data Warehouse Data Lake Data Governance Data Architecture 98

Cloudera

DECEMBER 1, 2023

These government-led efforts have had a profound impact on the development and adoption of AI solutions in the public sector, paving the way for a future where data-driven decision-making and automation are the norm. This requires a holistic approach that addresses the key areas of security, governance, and trustworthy data.

Data Governance 109

Data Governance Data-driven Strategy Data Architecture 109

IBM Big Data Hub

APRIL 27, 2022

Data fabric and data mesh are emerging data management concepts that are meant to address the organizational change and complexities of understanding, governing and working with enterprise data in a hybrid multicloud ecosystem. The good news is that both data architecture concepts are complimentary.

Management 79

Management Metadata Data Architecture Data Lake 79

CIO Business Intelligence

JUNE 27, 2022

Therefore, CIOs must be cautious about taking metrics at face value [and] leaders need to understand the data behind the metrics.”. When studying a metric, it’s important to know who created it and the data source. It’s important to understand the research and data behind the metrics,” Hurwitz says. Going it alone.

Metrics 133

Metrics KPI IT Consulting 133

BizAcuity

NOVEMBER 22, 2022

In today’s world that is largely data-driven, organizations depend on data for their success and survival, and therefore need robust, scalable data architecture to handle their data needs. For this reason, Snowflake is often the cloud-native data warehouse of choice. Introduction.

Data Warehouse 98

Data Warehouse Cost-Benefit Data Lake Internet of Things 98

AWS Big Data

FEBRUARY 26, 2025

Analytics remained one of the key focus areas this year, with significant updates and innovations aimed at helping businesses harness their data more efficiently and accelerate insights. From enhancing data lakes to empowering AI-driven analytics, AWS unveiled new tools and services that are set to shape the future of data and analytics.

Analytics 60

Analytics Data Lake Metadata Data Warehouse 60

CIO Business Intelligence

APRIL 5, 2022

Investment in data warehouses is rapidly rising, projected to reach $51.18 billion by 2028 as the technology becomes a vital cog for enterprises seeking to be more data-driven by using advanced analytics. Data warehouses are, of course, no new concept. More data, more demanding. “As

Data Warehouse 98

Data Warehouse Visualization Data-driven Data Architecture 98

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 127

Data Warehouse Analytics Data Lake Machine Learning 127

CIO Business Intelligence

AUGUST 2, 2023

A data and analytics capability cannot emerge from an IT or business strategy alone. With both technology and business organization deeply involved in the what, why, and how of data, companies need to create cross-functional data teams to get the most out of it. What are some examples of data solutions in each of those buckets?

Manufacturing 98

Manufacturing Data Architecture Data Strategy Strategy 98

BizAcuity

MAY 24, 2022

IaaS provides a platform for compute, data storage and networking capabilities. IaaS is mainly used for developing softwares (testing and development, batch processing), hosting web applications and data analysis. Analytics as a Service is almost a BI tool used for data analysis.and examples are restricted to the industry.

Data-driven 52

Data-driven Cost-Benefit Digital Transformation Strategy 52

Cloudera

SEPTEMBER 12, 2022

It sounds straightforward: you just need data and the means to analyze it. The data is there, in spades. Data volumes have been growing for years and are predicted to reach 175 ZB by 2025. First, organizations have a tough time getting their arms around their data. Unified data fabric. Yes and no.

Unstructured Data 75

Unstructured Data Data Architecture Data Lake Snapshot 75

CIO Business Intelligence

MAY 2, 2022

Can you deliver meaningful results on a data project within one or two quarters? That’s a requirement for nearly any initiative undertaken by Petco Chief Data and Analytics Officer Rakesh Srinivasan, who invests the talent and resources to achieve results quickly.

Advertising 98

Advertising Data Governance Insurance Data-driven 98

AWS Big Data

JUNE 10, 2024

Enterprises and organizations across the globe want to harness the power of data to make better decisions by putting data at the center of every decision-making process. However, throughout history, data services have held dominion over their customers’ data.

Data Lake 126

Data Lake Metadata Snapshot Analytics 126

Ontotext

JANUARY 10, 2024

Next, I will explain how knowledge graphs help them to get a unified view to data derived from multiple sources and get richer insights in less time. This requires new tools and new systems, which results in diverse and siloed data. And each of these gains requires data integration across business lines and divisions.

Metadata 72

Metadata Slice and Dice Data Integration Enterprise 72

BI-Survey

NOVEMBER 23, 2021

The existence of data silos is nothing new. Data-producing applications were once isolated systems. The transactional data was stored in isolated data sets and initially served only one purpose, namely, to document the transaction that had taken place. Over time, enterprises realized that data is worth more.

Digital Transformation 52

Digital Transformation Data Warehouse Data Lake Data-driven 52

Ontotext

DECEMBER 1, 2023

It enriched their understanding of the full spectrum of knowledge graph business applications and the technology partner ecosystem needed to turn data into a competitive advantage. Content and data management solutions based on knowledge graphs are becoming increasingly important across enterprises.

Metadata 78

Metadata Sales Machine Learning Consulting 78

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 84

Metadata Data Governance Digital Transformation Data Quality 84

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. In this post, we describe Orca’s journey building a transactional data lake using Amazon Simple Storage Service (Amazon S3), Apache Iceberg, and AWS Analytics.

Data Lake 98

Data Lake Analytics Snapshot Data Quality 98

AWS Big Data

FEBRUARY 9, 2023

Customers across industries seek meaningful insights from the data captured in their Customer Relationship Management (CRM) systems. To achieve this, they combine their CRM data with a wealth of information already available in their data warehouse, enterprise systems, or other software as a service (SaaS) applications.

Data Warehouse 101

Data Warehouse Data-driven Snapshot Testing 101

Alation

JULY 28, 2022

There was a time when most CIOs would never consider putting their crown jewels — AKA customer data and associated analytics — into the cloud. And what must organizations overcome to succeed at cloud data warehousing ? What Are the Biggest Drivers of Cloud Data Warehousing? The cloud is no longer synonymous with risk.

Data Warehouse 69

Data Warehouse Cost-Benefit Data-driven Data Governance 69

Cloudera

SEPTEMBER 7, 2023

There’s also the risk of various forms of data leakage, including intellectual property (IP) as well as personally identifiable information (PII) especially with commercial AI solutions. That said, Generative AI and LLMs appear to do all of these things, producing original, “creative” outputs by learning from input data.

Insurance 83

Insurance Risk Data-driven Finance 83

AWS Big Data

MARCH 26, 2024

This view is used to identify patterns and trends in customer behavior, which can inform data-driven decisions to improve business outcomes. 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.

Data Strategy 92

Data Strategy Strategy Data Warehouse Prescriptive Analytics 92

BizAcuity

APRIL 1, 2023

Introduction In today’s world that is largely data-driven, organizations depend on data for their success and survival, and therefore need robust, scalable data architecture to handle their data needs. For this reason, Snowflake is often the cloud-native data warehouse of choice.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Lake Internet of Things 52

erwin

SEPTEMBER 16, 2024

Continue to conquer data chaos and build your data landscape on a sturdy and standardized foundation with erwin® Data Modeler 14.0. The gold standard in data modeling solutions for more than 30 years continues to evolve with its latest release, highlighted by: PostgreSQL 16.x

Modeling 52

Modeling Visualization Data Governance Data Architecture 52

Ontotext

JANUARY 11, 2023

The implications of consumer behavior for retailers range from the need to ensure relevant customer service and quick delivery to serving personalized content and managing data from disparate systems. Of course, there are various platforms and data architectures for managing customer and product data. Click To Tweet.

Contextual Data 52

Contextual Data Interactive Data-driven Data Integration 52