CIO Business Intelligence

APRIL 29, 2022

Forward-thinking transformation leaders have realised that more focus needs to be placed on ‘data-centric value creation’ and have made this the pre-eminent organising principle in their organisations. Many organisations focus too heavily on fine tuning their computational models in their pursuit of ‘quick-wins.’ About Andrew P.

Data Governance 145

Data Governance IT Risk Data Lake 145

erwin

NOVEMBER 6, 2019

erwin released its State of Data Governance Report in February 2018, just a few months before the General Data Protection Regulation (GDPR) took effect. Download Free GDPR Guide | Step By Step Guide to Data Governance for GDPR?. How to automate data mapping. The Role of Data Automation. We wonder why.

Metadata 102

Metadata Data Governance Management Cost-Benefit 102

erwin

JANUARY 17, 2020

What is Data Modeling? Data modeling is a process that enables organizations to discover, design, visualize, standardize and deploy high-quality data assets through an intuitive, graphical interface. Data models provide visualization, create additional metadata and standardize data design across the enterprise.

Data-driven 138

Data-driven Modeling Metadata Data Governance 138

Alation

JANUARY 20, 2022

In Ryan’s “9-Step Process for Better Data Quality” he discussed the processes for generating data that business leaders consider trustworthy. To be clear, data quality is one of several types of data governance as defined by Gartner and the Data Governance Institute. Step 4: Data Sources.

Data Quality 94

Data Quality Data Governance Metrics Statistics 94

Data Virtualization

FEBRUARY 22, 2024

Reading Time: 6 minutes The emergence of Large Language Models (LLMs) and Generative AI marks a significant leap in technology, promising to deliver transformational automation and innovation across diverse industries and use cases. Having said that, as everyone races to develop next generation AI.

Modeling 69

Modeling Data Integration Management Technology 69

erwin

JANUARY 24, 2019

In most companies, an incredible amount of data flows from multiple sources in a variety of formats and is constantly being moved and federated across a changing system landscape. They need their data mappings to fall under governance and audit controls, with instant access to dynamic impact analysis and lineage.

Data Governance 71

Data Governance Metadata Data-driven Cost-Benefit 71

Alation

JUNE 2, 2022

In part one of this series, I discussed how data management challenges have evolved and how data governance and security have to play in such challenges, with an eye to cloud migration and drift over time. These include tracking, documenting, monitoring, versioning, and controlling access to AI/ML models.

Modeling 52

Modeling Data Governance Statistics Unstructured Data 52

erwin

MAY 14, 2021

Accelerating the retrieval and analysis of data —so much of it unstructured—is vital to becoming a data-driven business that can effectively respond in real time to customers, partners, suppliers and other parties, and profit from these efforts. The Newest Release of erwin Data Modeler.

Modeling 80

Modeling Digital Transformation Data-driven Optimization 80

CIO Business Intelligence

APRIL 1, 2024

Data preparation, including anonymizing, labeling, and normalizing data across sources, is key. You’ll also institute guardrails for data governance, data quality, data integrity, and data security. Right-size your model(s). Choose a workload location. 2024 Artificial Intelligence

Data Lake 142

Data Lake Consulting Uncertainty Risk 142

CIO Business Intelligence

JANUARY 24, 2024

“IT leaders should establish a process for continuous monitoring and improvement to ensure that insights remain actionable and relevant, by implementing regular review cycles to assess the effectiveness of the insights derived from unstructured data.” This type of environment can also be deeply rewarding for data and analytics professionals.”

Data Strategy 136

Data Strategy Strategy Unstructured Data Data Governance 136

erwin

JANUARY 3, 2019

With this in mind, the erwin team has compiled a list of the most valuable data governance, GDPR and Big data blogs and news sources for data management and data governance best practice advice from around the web. Top 7 Data Governance, GDPR and Big Data Blogs and News Sources from Around the Web. . —

Data Governance 53

Data Governance Big Data Data-driven Data Processing 53

O'Reilly on Data

FEBRUARY 4, 2019

In this post, I’ll describe some of the key areas of interest and concern highlighted by respondents from Europe, while describing how some of these topics will be covered at the upcoming Strata Data conference in London (April 29 - May 2, 2019). Data Platforms. Data Integration and Data Pipelines.

Machine Learning 277

Machine Learning Enterprise IoT Big Data 277

Cloudera

DECEMBER 1, 2023

Lastly, trustworthy data forms the foundation of any AI solution. Governments must ensure that the data used for training AI models is of high quality, accurately representing the diverse range of scenarios and demographics it seeks to address.

Data Governance 105

Data Governance Data-driven Strategy Data Architecture 105

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. But the attempts to standardize data across the entire enterprise haven’t produced the desired results.

Data Governance 40

Data Governance Risk Metadata Management 40

IBM Big Data Hub

JUNE 29, 2023

Data integration and analytics IBP relies on the integration of data from different sources and systems. This may involve consolidating data from enterprise resource planning (ERP) systems, customer relationship management (CRM) systems, supply chain management systems, and other relevant sources.

Key Performance Indicator 81

Key Performance Indicator Forecasting Data Integration Sales 81

erwin

APRIL 27, 2022

Best Data Governance Solution (erwin Data Intelligence). Best Data Modeling Solution (erwin Data Modeler). Best Data Security Solution (Quest ApexSQL). Best Data Governance Solution (erwin Data Intelligence). Best Data Governance Solution (erwin Data Intelligence).

Data Governance 52

Data Governance Digital Transformation Metadata Data Warehouse 52

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

Cloudera

MAY 9, 2019

The report created a readiness model with five dimensions and various metrics under each dimension. The five dimensions of the readiness model are –. Data readiness – These set of metrics help you measure if your organization is geared up to handle the sheer volume, variety and velocity of IoT data. See you there!

IoT 53

IoT Modeling Metrics Measurement 53

CIO Business Intelligence

NOVEMBER 21, 2023

Set parameters and emphasize collaboration To address one root cause of shadow IT, CIOs must also establish a governance and delivery model for evaluating, procuring, and implementing department technology solutions. There may be times when department-specific data needs and tools are required.

IT 137

IT Risk Cost-Benefit Risk Management 137

CIO Business Intelligence

NOVEMBER 17, 2022

A key component to the appeal of cloud-first business models is cloud technologies’ ability to simplify processes and streamline workflows through integration and automation. This is especially true for content management operations looking to navigate the complexities of data compliance while getting the most from their data.

Software 144

Software Management Digital Transformation Data Governance 144

CIO Business Intelligence

AUGUST 2, 2023

The third and most complicated layer is architecture and governance, which we’ve linked together as one layer. The last layer is raw data, which is where we get the data out of the source systems, organize it, secure it, and figure out which data lakes to use. These aren’t typically business discussions; it’s largely IT.

Manufacturing 98

Manufacturing Data Architecture Strategy Data Strategy 98

IBM Big Data Hub

JUNE 23, 2022

The ability to compose and re-use data services with IBM’s data fabric on IBM Cloud Pak for Data allows you to tackle a variety of use cases such as multi-cloud data integration, governance and privacy, customer 360, and MLOps and Trustworthy AI.

Enterprise 52

Enterprise Metadata Data Governance Machine Learning 52

O'Reilly on Data

FEBRUARY 11, 2019

Foundational data technologies. Machine learning and AI require data—specifically, labeled data for training models. Data lineage, data catalog, and data governance solutions can increase usage of data systems by enhancing trustworthiness of data. Data Platforms.

Big Data 209

Big Data Technology Machine Learning Deep Learning 209

CIO Business Intelligence

FEBRUARY 16, 2023

Hence the drive to provide ML as a service to the Data & Tech team’s internal customers. All they would have to do is just build their model and run with it,” he says. That step, primarily undertaken by developers and data architects, established data governance and data integration.

Unstructured Data 105

Unstructured Data Data Lake Prescriptive Analytics Digital Transformation 105

IBM Big Data Hub

NOVEMBER 4, 2022

Why does data quality matter across the data lifecycle? Data quality issues can have far-reaching consequences across the lifecycle of data: 1. When a sophisticated AI/ML model confronts bad-quality data, it is the latter that usually wins. Data Governance. Analytics and AI.

Data Quality 57

Data Quality Metadata Data Governance Data-driven 57

CIO Business Intelligence

MAY 2, 2022

On May 11, we’ll look at one of the most high-profile new consumer use cases of data: sports betting. Darren Rovell, a senior producer at Action Network and a former journalist at ESPN and CNBC , will share how sophisticated data newly available to bettors is equalizing the playing field with sports books.

Advertising 98

Advertising Data Governance Insurance Strategy 98

FineReport

APRIL 9, 2024

Challenges in Data Management Data Security and Compliance The protection of sensitive patient information and adherence to regulatory standards pose significant challenges in healthcare data management. This foundational approach is vital for reliable decision-making based on trustworthy information derived from BI tools.

Digital Transformation 52

Digital Transformation Business Intelligence Data-driven Visualization 52

IBM Big Data Hub

MAY 9, 2022

Others have come into sharper focus relatively recently: a global effort to create new data privacy laws, a post-pandemic expectation by customers to know them individually across all touchpoints, and increased attention on any racial, gender-based, or socioeconomic bias in AI models. Multicloud data integration.

Management 57

Management Data Quality Metadata Data Integration 57

IBM Big Data Hub

JULY 6, 2022

In addition to data observability, IBM clients can take advantage of use cases such as multicloud data integration, data governance and privacy, customer 360, and MLOps and trustworthy AI. Data observability will also integrate with these other use cases for improved results where both are applied.

Metadata 57

Metadata Data Quality Snapshot Cost-Benefit 57

erwin

JANUARY 17, 2019

Data governance is more important to the enterprise than ever before. It ensures everyone in the organization can discover and analyze high-quality data to quickly deliver business value. A mature and sustainable data governance initiative must include data integration.

Metadata 63

Metadata Data Governance Data Quality Data-driven 63

CIO Business Intelligence

JANUARY 5, 2024

From an organizational standpoint, we evolved to a nearshore model, attracting the necessary talent that new technologies required. With that, we adopted an onshore model and created a center of excellence in Madrid where we manage all operations and lead all implementation projects worldwide. How have you rebuilt all the IT talent?

IT 116

IT Finance Cost-Benefit Strategy 116

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 52

Metadata Data Governance Digital Transformation Data Quality 52

DataKitchen

OCTOBER 2, 2023

Whether the Data Ingestion Team struggles with fragmented database ownership and volatile data environments or the End-to-End Data Product Team grapples with real-time data observability issues, the article provides actionable recommendations. ’ What’s a Data Journey?

Data Quality 100

Data Quality Testing Uncertainty Data Enablement 100

Data Virtualization

JUNE 8, 2023

Disruptive, large language model (LLM) technologies like ChatGPT, OPT, CodeGen, and PaLM 2 are about to transform both the way we communicate with applications and. Reading Time: 3 minutes Artificial intelligence (AI) technologies are poised to bring about a revolution in the business world.

Data Integration 52

Data Integration Technology Modeling Management 52

IBM Big Data Hub

DECEMBER 16, 2022

Because Alex can use a data catalog to search all data assets across the company, she has access to the most relevant and up-to-date information. She can search structured or unstructured data, visualizations and dashboards, machine learning models, and database connections. Protected and compliant data.

Metadata 52

Metadata Data Quality Data-driven Data Governance 52

CDW Research Hub

JANUARY 28, 2022

Leverage cloud in the hybrid model. Storage solutions must be agile, and that’s why many organizations are adopting hybrid cloud solutions to accommodate changes in application and data growth. With a multi-cloud strategy, organizations get the flexibility to collect, segregate and store data whether it’s on- or off-premises.

Digital Transformation 86

Digital Transformation Data-driven IoT Optimization 86

FineReport

APRIL 9, 2024

Evolving BI Tools in 2024 Significance of Business Intelligence In 2024, the role of business intelligence software tools is more crucial than ever, with businesses increasingly relying on data analysis for informed decision-making. This resulted in increased profitability and strengthened competitive positioning within the industry.

Business Intelligence 52

Business Intelligence Software Data-driven Predictive Modeling 52