Alation

JULY 15, 2022

I recently led an online session, Data Monetisation and Governance , looking at the evolution of data governance , defining data ethics (from the Turing Institute ), and touching on the balancing act between using data to monetise (by increasing revenue, decreasing spend, or mitigating risk) and meeting ethical obligations.

Cost-Benefit 89

Cost-Benefit Data Governance ROI Risk 89

AWS Big Data

FEBRUARY 29, 2024

Data is your generative AI differentiator, and a successful generative AI implementation depends on a robust data strategy incorporating a comprehensive data governance approach. Data governance is a critical building block across all these approaches, and we see two emerging areas of focus.

Data Governance 98

Data Governance Unstructured Data Metadata Data Lake 98

Alation

SEPTEMBER 9, 2021

And throughout the year, your Asset-Liability Committee (ALCO) also reviews risks from a balance sheet and market perspective. If you want to use analytics as part of this review, you need data governance. Whether you’re looking at market share or stock prices, you want to use all the data possible (both structured and unstructured).

Data Governance 52

Data Governance Data Strategy Strategy Risk 52

CIO Business Intelligence

OCTOBER 24, 2023

One easy step to get teams started on the right foot is to document and communicate a vision statement with stakeholders and selected end-users before beginning. CIOs must ensure security and compliance experts are plugged in and collaborate effectively with all teams involved in digital transformation initiatives.

Digital Transformation 145

Digital Transformation Data-driven Business Objectives Strategy 145

CIO Business Intelligence

SEPTEMBER 14, 2022

technologies that fueled data strategies aimed at identifying inefficiencies, streamlining processes, and improving the ability to forecast and predict industry trends. Data scientists are critical in manufacturing because they help businesses collect, manage, and store relevant data for customers, clients, products, and services.

Manufacturing 116

Manufacturing IT Software Digital Transformation 116

erwin

JANUARY 17, 2020

Companies that want to advance artificial intelligence (AI) initiatives, for instance, won’t get very far without quality data and well-defined data models. With the right approach, data modeling promotes greater cohesion and success in organizations’ data strategies. But what is the right data modeling approach?

Data-driven 138

Data-driven Modeling Metadata Data Governance 138

CIO Business Intelligence

JANUARY 24, 2024

“Our analytics capabilities identify potentially unsafe conditions so we can manage projects more safely and mitigate risks.” There’s also investment in robotics to automate data feeds into virtual models and business processes. Put your data strategy in business turns. Hire the right architects.

Risk Management 118

Risk Management Risk Management Digital Transformation 118

Alation

OCTOBER 5, 2021

Yet, so many companies today are still failing miserably in implementing data strategy and governance protocols. Why is your data governance strategy failing? So, why is YOUR data governance strategy failing? Common data governance challenges. Top 3 Roadblocks to Successful Data Governance.

Data Governance 96

Data Governance Strategy Data Quality Metrics 96

CIO Business Intelligence

MARCH 8, 2023

The reality is many organisations still struggle with the data and analytics foundations required to progress down an advanced AI path. Infosys research found 63 per cent of AI models function at basic capability only, are driven by humans, and often fall short on data verification, data practices and data strategies.

Enterprise 52

Enterprise Data Governance Data Strategy Testing 52

Ontotext

MAY 2, 2024

They are expected to understand the entire data landscape and generate business-moving insights while facing the voracious needs of different teams and the constraints of technology architecture and compliance. Evolution of data approaches The data strategies we’ve had so far have led to a lot of challenges and pain points.

Metadata 52

Metadata Data Lake Data-driven Enterprise 52

Ontotext

MARCH 8, 2023

However, this information is typically stored in disparate locations, often hidden within departmental documents or applications. Use Case #4: Financial Risk Detection and Prediction The financial industry is made up of a network of markets and transactions. Which financial institutions have filed similar risk compliance issues?

Enterprise 52

Enterprise Knowledge Discovery Risk Data-driven 52

datapine

JANUARY 24, 2021

Additionally, you want to clarify these questions regarding data analysis now or as soon as possible – which will make your future business intelligence much clearer. These are good questions to ask when looking at a data set but not only, as you can develop a good and complete data-strategy if you utilize them as a whole.

IT 317

IT Statistics KPI Data-driven 317

Cloudera

NOVEMBER 30, 2020

That growing dependence means a treasure trove of data — especially personally sensitive or identifiable data— is moving online. . But as data and regulation of data grows, compliance departments are seeing cuts, adding even more risk. Data Strategy . Cloudera Data Platform (CDP).

Data Strategy 67

Data Strategy Strategy Risk Data Architecture 67

CIO Business Intelligence

MARCH 21, 2022

Unfortunately, they have fallen behind when it comes to automation and data integration practices, despite industry-wide recognition of the merits associated with an effective data strategy,” said Wayne Johnson , CEO & Founder of Encompass. Lost productivity.

Data-driven 116

Data-driven IT Finance Forecasting 116

Domino Data Lab

APRIL 3, 2019

Probably the best one-liner I’ve encountered is the analogy that: DG is to data assets as HR is to people. Also, while surveying the literature two key drivers stood out: Risk management is the thin-edge-of-the-wedge ?for Now’s the time to get in on the ground floor of how to “ leverage data as a strategic asset ” in the US.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

AWS Big Data

JULY 28, 2023

Data dependencies – Personal data can be interconnected and intertwined with other data systems, making it challenging to remove specific data without impacting the integrity of functionality of other systems or processes. Ensuring the complete removal of data from all these copies and backups can be challenging.

Snapshot 82

Snapshot Metadata Measurement Data Warehouse 82

AWS Big Data

FEBRUARY 27, 2023

Data sharing is becoming an important element of an enterprise data strategy. AWS services like AWS Data Exchange provide an avenue for companies to share or monetize their value-added data with other companies. This pattern discusses an approach to sharing such documents.

Enterprise 88

Enterprise Publishing Data Lake Management 88

Alation

MARCH 28, 2023

With data becoming more prevalent in every industry, organisations have to determine how to not only manage it but also drive value from it. The MoD identify three key issues: firstly, that ‘Defence data operates in contractual, technical and behavioural silos’. The defence industry is no exception.

Metadata 52

Metadata Data Strategy Data Quality Strategy 52

Alation

MAY 31, 2023

Their broad range of responsibilities include: Design and implement data architecture. Maintain data models and documentation. Ensure data security and compliance. Define data requirements and policies. Select and implement data tools and technologies. Identify and address data issues.

Data Governance 52

Data Governance Metadata Data Architecture Data Quality 52

Alation

MARCH 21, 2023

Data security The travel industry collects, transmits, processes, and stores a wide range of personally identifiable information (PII) from customers, which are of interest to bad actors, as cybercriminals target this valuable data. Otherwise, they risk a data privacy violation. Curious to see Alation in action?

Data Analytics 52

Data Analytics Analytics Data-driven Big Data 52

BI-Survey

NOVEMBER 23, 2021

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. Data-based insights are being used to automate decisions. BARC RECOMMENDATION.

Digital Transformation 52

Digital Transformation Data Warehouse Data Lake Data-driven 52

Cloudera

NOVEMBER 25, 2020

For example, it includes patient samples (blood, blood pressure, temperature, and more), patient information (age, gender, where they have lived, family situation, and other details), and treatment history, most of which is currently found only in paper documents.

Data Warehouse 58

Data Warehouse Unstructured Data Analytics Visualization 58

Grooper

AUGUST 19, 2019

Master data management. Data governance. Scoring – i.e. profitability or risk. Structured, semi-structured, and unstructured data. Data pipelines. Banks use analytics to differentiate customers and align product offerings based on credit risk, usage, and other characteristics. Databases, tables, and columns.

Analytics 54

Analytics Machine Learning Data Science Data-driven 54

Alation

DECEMBER 15, 2021

This uncovers actionable intelligence, maintains compliance with regulations, and mitigates risks. Let’s explore the key steps for building an effective data governance strategy. What is a Data Governance Strategy? A data governance strategy provides a framework that connects people to processes and technology.

Data Governance 52

Data Governance Strategy Metadata Data Strategy 52

Sisense

JULY 23, 2021

Not only does it support the successful planning and delivery of each edition of the Games, but it also helps each successive OCOG to develop its own vision, to understand how a host city and its citizens can benefit from the long-lasting impact and legacy of the Games, and to manage the opportunities and risks created.

Unstructured Data 105

Unstructured Data Internet of Things Data-driven Data Processing 105

Alation

FEBRUARY 10, 2022

Data classification is necessary for leveraging data effectively and efficiently. Effective data classification helps mitigate risk, maintain governance and compliance, improve efficiencies, and help businesses understand and better use data. Mitigate Security Risk. Content-Based Classification.

Data Governance 52

Data Governance Risk Insurance Strategy 52

AWS Big Data

AUGUST 14, 2023

At the same time, unstructured approaches to data mesh management that don’t have a vision for what types of products should exist and how to ensure they are developed are at high risk of creating the same effect through simple neglect. When do new data products get created, and who is allowed to create them?

Management 78

Management Risk Measurement Optimization 78

Alation

JULY 6, 2021

There are new ways to quickly and effectively overcome these data governance challenges. A person or team with influence must take responsibility for reducing data governance risks. They should have resources, tools for connectivity and integration, and insights into data usage and needs. No Data Leadership.

Data Governance 52

Data Governance Metadata Data Quality Risk 52

Alation

MAY 10, 2021

Implementing a data catalog enhances an organization’s data management and allows for the democratization of that data But how are data catalogs implemented? In phase one, an enterprise must create a data strategy , which will inform later plans. Build a Data Strategy (Phase One).

Strategy 80

Strategy Enterprise Data Strategy Data Governance 80

Alation

NOVEMBER 22, 2022

A well-governed data landscape enables data users in the public sector to better understand the driving forces and needs to support public policy – and measure impact once a change is made. Efficient Access To Data. Citizens, companies, and government employees need access to data and documents. Reduces Fraud.

Data Governance 52

Data Governance Metadata Data-driven Unstructured Data 52

Alation

OCTOBER 12, 2021

.” Gilbert further breaks down the data challenges Cbus faced, saying: “[Another] challenge was around understanding the data. We might have found some data but what does it mean? There was a lack of documentation and a very heavy reliance on IT and business SMEs. Time spent managing data.

Strategy 52

Strategy Enterprise Analytics Data Governance 52

Jet Global

OCTOBER 4, 2023

Finance teams are under pressure to slash costs while playing a key role in data strategy, yet they are still bogged down by manual tasks, overreliance on IT, and low visibility on company data. This expansion of responsibilities is exacerbating the well-documented trend of finance team burnout, leading to undesirable turnover.

Finance 52

Finance Reporting Cost-Benefit Management 52