CIO Business Intelligence

JANUARY 9, 2024

The October 2023 CEO Outlook Pulse from professional services firm EY reported that 99% of chief executives were planning to invest in generative AI. That’s the question many CIOs are asking, as some report they are now the ones raising points about business needs and business value whenever there’s a demand for an AI solution.

IT 130

IT Risk Cost-Benefit Enterprise 130

Alation

SEPTEMBER 7, 2021

In this blog we will discuss how Alation helps minimize risk with active data governance. Now that you have empowered data scientists and analysts to access the Snowflake Data Cloud and speed their modeling and analysis, you need to bolster the effectiveness of your governance models. Find Trusted Data.

Data Governance 59

Data Governance Risk Data Quality Dashboards 59

Octopai

MAY 15, 2023

Data lineage helps identify redundant or inefficient data integration steps, allowing organizations to streamline their processes and reduce development, maintenance, and operational costs associated with ETL. Data quality costs: Poor data quality can result in significant costs for organizations.

Data Quality 52

Data Quality Data Governance Data Integration Risk 52

datapine

APRIL 15, 2020

It’s necessary to say that these processes are recurrent and require continuous evolution of reports, online data visualization , dashboards, and new functionalities to adapt current processes and develop new ones. Working software over comprehensive documentation. Discover the available data sources.

Business Intelligence 276

Business Intelligence Analytics Testing Dashboards 276

erwin

SEPTEMBER 17, 2020

According to erwin’s “2020 State of Data Governance and Automation” report , close to 70 percent of data professional respondents say they spend an average of 10 or more hours per week on data-related activities, and most of that time is spent searching for and preparing data.

Cost-Benefit 143

Cost-Benefit Data Governance Metadata Reporting 143

Grooper

APRIL 9, 2020

The heart of digital transformation is data, and organizations without a clear strategy for data curation and enrichment from documents are at risk of failed transformation and missing out on massive revenue opportunities. The way we’ve thought about curating data from documents over the years is fundamentally flawed.

Digital Transformation 65

Digital Transformation Data Quality Enterprise Risk 65

erwin

FEBRUARY 13, 2020

The numerous data types and data sources that exist today weren’t designed to work together, and data infrastructures have been cobbled together over time with disparate technologies, poor documentation and little thought for downstream integration. Finding metadata, “the data about the data,” isn’t easy.

Metadata 135

Metadata Data Governance Management Cost-Benefit 135

Alation

AUGUST 17, 2022

We’ve seen the emergence of new, less invasive approaches, yet the question remains: What do CIOs think is most required to deliver a successful data governance program? The Risks of Early Data Governance Programs. The biggest risk was a lack of ownership. If your definitions are bad, so is your governance/risk/security.

Data Governance 92

Data Governance Risk Data-driven Measurement 92

erwin

JANUARY 11, 2019

A company can’t effectively implement data governance – documenting and applying business rules and processes, analyzing the impact of changes and conducting audits – if it fails at data management. The problem usually starts by relying on manual integration methods for data preparation and mapping.

Data Governance 40

Data Governance Risk Metadata Management 40

Octopai

JANUARY 19, 2020

BCBS 239 is a document published by that committee entitled, Principles for Effective Risk Data Aggregation and Risk Reporting. The document organizes the best practices into a set of 14 principles. – Principle 3 contains data accuracy and integrity rules. What BCBS 239 Does.

Metadata 61

Metadata Risk Management Business Intelligence Data Governance 61

erwin

JANUARY 30, 2020

The 2020 State of Data Governance and Automation (DGA) report is a follow-up to an initial survey we commissioned two years ago to explore data governance ahead of the European Union’s General Data Protection Regulation (GDPR) going into effect. 1 reason to implement data governance.

Data Governance 145

Data Governance Metadata Cost-Benefit Digital Transformation 145

DataKitchen

FEBRUARY 21, 2023

are more efficient in prioritizing data delivery demands.” Release New Data Engineering Work Often With Low Risk: “Testing and release processes are heavily manual tasks… automate these processes.” Learn, improve, and iterate quickly (with feedback from the customer) with low risk.

Data-driven 130

Data-driven Testing Risk Cost-Benefit 130

Alation

FEBRUARY 14, 2023

In this day and age, regardless of industry, keeping data protected and its uses understood is vital. No business wants to have the PR nightmare of a data leak or personal data being used without the correct permissions. This is where successful data governance programs can act as a savior to many organizations.

Data Governance 52

Data Governance ROI Metrics Cost-Benefit 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

CIO Business Intelligence

MARCH 24, 2023

Overcoming data challenges Despite their growing commitment to ESG, financial firms have learned the path to sustainability and prosperity can be rocky. “ESG ESG data quality is the biggest challenge. revenue growth from businesses showing a lower commitment to ESG. Emerging technologies will further speed ESG progress.

Risk Management 52

Risk Management Consulting Metrics Data Quality 52

Alation

APRIL 18, 2023

For any data user in an enterprise today, data profiling is a key tool for resolving data quality issues and building new data solutions. In this blog, we’ll cover the definition of data profiling, top use cases, and share important techniques and best practices for data profiling today.

IT 52

IT Metadata Data Quality Data Governance 52

AWS Big Data

MARCH 1, 2024

One of the bank’s key challenges related to strict cybersecurity requirements is to implement field level encryption for personally identifiable information (PII), Payment Card Industry (PCI), and data that is classified as high privacy risk (HPR). Only users with required permissions are allowed to access data in clear text.

Data Lake 95

Data Lake Data Warehouse Management Risk 95

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

Ontotext

MAY 2, 2024

Data products – optimization of data assets that drive business, improving data quality and interoperability. It took 4 months from deciding that a drug was valuable to submitting the report. Another complication was the existing data silos.

Metadata 52

Metadata Data Lake Data-driven Enterprise 52

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? Inconsistencies in expectations can create enormous negative issues regarding data quality and governance.

Data Governance 96

Data Governance Strategy Data Quality Metrics 96

datapine

JANUARY 24, 2021

This can include a multitude of processes, like data profiling, data quality management, or data cleaning, but we will focus on tips and questions to ask when analyzing data to gain the most cost-effective solution for an effective business strategy. 4) How can you ensure data quality?

IT 317

IT Statistics KPI Data-driven 317

Ontotext

MAY 22, 2023

At the heart of such tools is the extraction of fields from forms or specific attributes from documents. Luckily, the text analysis that Ontotext does is focused on tasks that require complex domain knowledge and linking of documents to reference data or master data. That’s something that LLMs cannot do.

Management 59

Management Unstructured Data Metadata Cost-Benefit 59

Smart Data Collective

JULY 15, 2021

It helps you locate and discover data that fit your search criteria. With data catalogs, you won’t have to waste time looking for information you think you have. What Does a Data Catalog Do? Advanced data catalogs can update metadata based on the data’s origins. How Does a Data Catalog Impact Employees?

Metadata 127

Metadata IT Data-driven Data Quality 127

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

Jet Global

MAY 1, 2020

Recently released is a report by Gartner about all the things that can go wrong in your BI implementation. In Gartner’s report, an analyst goes to great pains to say that there is “much more risk associated to non-technology issues than there is to deploying the infrastructure, tools, and apps.”. Risk to the business.

Data Warehouse 64

Data Warehouse Data Quality Risk Reporting 64

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 75

Management Risk Measurement Optimization 75

O'Reilly on Data

DECEMBER 12, 2019

1] This includes C-suite executives, front-line data scientists, and risk, legal, and compliance personnel. These recommendations are based on our experience, both as a data scientist and as a lawyer, focused on managing the risks of deploying ML. Currency amounts reported in Taiwan dollars. Sensitivity analysis.

Machine Learning 191

Machine Learning Modeling Testing Risk Management 191

O'Reilly on Data

OCTOBER 22, 2020

It’s also a good indirect measure of training data quality: a team that does not know where their data originated is likely to not know other important details about the data as well. All this because they quoted a reporter who writes about automated content moderation.

Consulting 296

Consulting Risk Cost-Benefit Modeling 296

O'Reilly on Data

JULY 28, 2020

Many companies face a problem that’s even worse: no one knows which levers contribute to the metrics that impact business outcomes, or which metrics are important to the company (such as those reported to Wall Street by publicly-traded companies). Acquiring data is often difficult, especially in regulated industries.

Marketing 362

Marketing Experimentation Metrics Testing 362

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

Jet Global

MARCH 13, 2020

Traditionally, this meant tracking a small set of numbers at occasional intervals, such as in the month-end close or the quarterly financial report. That includes things like reading financial statements, balance sheets, and cash flow reports. They prefer to ask an accountant or someone from IT to retrieve data for them.

Finance 64

Finance Snapshot Reporting Uncertainty 64

erwin

APRIL 15, 2020

If we reflect on the coronavirus example, we can ask: How do individual countries report their data? Are asymptomatic infections reported? In our businesses, it is vital that we work to develop a deeper understanding of the sources, methods and quality of incoming third-party data.

Data Governance 134

Data Governance Metadata Testing Reporting 134

CIO Business Intelligence

JANUARY 30, 2024

Corporate ESG reporting is getting real for companies around the globe. Enacted and proposed regulations in the EU, US, and beyond are deepening reporting requirements in an effort to change business behavior. The foundation for ESG reporting, of course, is data. The foundation for ESG reporting, of course, is data.

Reporting 109

Reporting Data Quality Strategy Data-driven 109

FineReport

APRIL 26, 2023

The Big Data ecosystem is rapidly evolving, offering various analytical approaches to support different functions within a business. ” This type of Analytics includes traditional query and reporting settings with scorecards and dashboards. Top 10 Big Data Tools 1. The most distinct is its reporting capabilities.

Big Data 52

Big Data Data Analytics Analytics Cost-Benefit 52

O'Reilly on Data

NOVEMBER 28, 2023

As of November 2023: Two-thirds (67%) of our survey respondents report that their companies are using generative AI. AI users say that AI programming (66%) and data analysis (59%) are the most needed skills. Unexpected outcomes, security, safety, fairness and bias, and privacy are the biggest risks for which adopters are testing.

Enterprise 271

Enterprise Modeling Testing Reporting 271

O'Reilly on Data

JULY 15, 2019

After the 2008 financial crisis, the Federal Reserve issued a new set of guidelines governing models— SR 11-7 : Guidance on Model Risk Management. Note that the emphasis of SR 11-7 is on risk management.). Sources of model risk. Machine learning developers are beginning to look at an even broader set of risk factors.

Machine Learning 38

Machine Learning Management Enterprise Risk Management 38

Octopai

JUNE 24, 2019

“Data governance” is data management policy that ensures the integrity, availability, and efficiency of data within a company. This policy includes specialists, processes, and technology used to manage data. Document classification and lifecycle management will help you deal with oversight of unstructured data.

Data Governance 42

Data Governance Metadata Unstructured Data Software 42