CIO Business Intelligence

MAY 3, 2022

I would rather have a few focused areas that are impactful for the business, where we can significantly make improvement, rather than hundreds of areas and barely make progress. By focusing on a few areas that are aligned to our business objectives, we get wins for the company, our customers, and our people.

Data Quality 96

Data Quality Machine Learning Business Objectives Business Intelligence 96

erwin

MAY 27, 2020

Data modeling supports collaboration among business stakeholders – with different job roles and skills – to coordinate with business objectives. Data resides everywhere in a business , on-premise and in private or public clouds. Nine Steps to Data Modeling.

Modeling 98

Modeling Metadata Data Governance Visualization 98

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

erwin

JULY 12, 2019

The complexity of regulatory requirements in and of themselves is aggravated by the complexity of the business and data landscapes within most enterprises. Creating and automating a curated enterprise data catalog , complete with physical assets, data models, data movement, data quality and on-demand lineage.

Data Governance 110

Data Governance Management Metadata Risk Management 110

CIO Business Intelligence

APRIL 6, 2022

In all of these roles, I’ve come across patterns that enable organizations to build faster business insights and innovation with data. These patterns encompass a way to deliver value to the business with data; I refer to them collectively as the “data operating model.” 2) The real-time data pattern.

Cost-Benefit 135

Cost-Benefit Digital Transformation Data-driven Strategy 135

Jen Stirrup

SEPTEMBER 30, 2021

They may also learn from evidence, but the data and the modelling fundamentally comes from humans in some way. Data Science – Data science is the field of study that combines domain expertise, programming skills, and knowledge of mathematics and statistics to extract meaningful insights from data.

Business Intelligence 135

Business Intelligence Data mining Machine Learning Testing 135

BizAcuity

NOVEMBER 13, 2024

Challenges in Achieving Data-Driven Decision-Making While the benefits are clear, many organizations struggle to become fully data-driven. Challenges such as data silos, inconsistent data quality, and a lack of skilled personnel can create significant barriers.

Consulting 52

Consulting Data-driven Cost-Benefit Business Intelligence 52

DataRobot Blog

MAY 26, 2022

Last time , we discussed the steps that a modeler must pay attention to when building out ML models to be utilized within the financial institution. In summary, to ensure that they have built a robust model, modelers must make certain that they have designed the model in a way that is backed by research and industry-adopted practices.

Risk 52

Risk Modeling Metrics Business Objectives 52

CIO Business Intelligence

MAY 7, 2024

That’s according to a recent report based on a survey of CDOs by AWS in conjunction with the Chief Data Officer and Information Quality (CDOIQ) Symposium. The CDO position first gained momentum around 2008, to ensure data quality and transparency to comply with regulations following the housing credit crisis of that era.

Data Strategy 131

Data Strategy Data-driven Data Quality Data Governance 131

IBM Big Data Hub

FEBRUARY 9, 2023

The primary goal of any data governance program is to deliver against prioritized business objectives and unlock the value of your data across your organization. Realize that a data governance program cannot exist on its own – it must solve business problems and deliver outcomes.

Data Governance 76

Data Governance Business Objectives Data Quality Measurement 76

CIO Business Intelligence

MAY 30, 2024

Using data and algorithms to imitate the way humans learn came into the scene in the 1980s, and this further evolved to deep learning in the 2000s. Accelerated computing has led to the creation and scaling of large language models that have now democratized AI, finding ChatGPT a place in the dictionary.

Data Quality 104

Data Quality Key Performance Indicator Digital Transformation Management 104

CIO Business Intelligence

JUNE 23, 2023

According to the MIT Technology Review Insights Survey, an enterprise data strategy supports vital business objectives including expanding sales, improving operational efficiency, and reducing time to market. The problem is today, just 13% of organizations excel at delivering on their data strategy.

Data Strategy 116

Data Strategy Strategy Visualization Consulting 116

CIO Business Intelligence

NOVEMBER 13, 2023

Failure to align technology capabilities with business goals can result in a wasted investment in technology that doesn’t support business objectives. Transformational leaders must ensure their organizations have the right systems and processes in place to collect, store, and analyze data effectively.

Digital Transformation 143

Digital Transformation Cost-Benefit Experimentation Measurement 143

CIO Business Intelligence

NOVEMBER 2, 2023

Still, 94% of technical leaders say they should be getting more value from their data and 78% say their organizations struggle to drive business priorities with data. But if that’s not tied to the IT team and they’re not thinking the way that I think, it’s very hard to actually have an aligned strategy.”

Data Strategy 137

Data Strategy Strategy Sales Data Governance 137

CIO Business Intelligence

APRIL 4, 2024

“Everyone is running around trying to apply this technology that’s moving so fast, but without business outcomes, there’s no point to it,” says Redmond, CIO at power management systems manufacturer Eaton Corp. “We We need to continue to be mindful of business outcomes and apply use cases that make sense.”

Enterprise 134

Enterprise Cost-Benefit Forecasting Sales 134

AWS Big Data

MARCH 26, 2024

A Gartner Marketing survey found only 14% of organizations have successfully implemented a C360 solution, due to lack of consensus on what a 360-degree view means, challenges with data quality, and lack of cross-functional governance structure for customer data.

Data Strategy 102

Data Strategy Strategy Data Warehouse Prescriptive Analytics 102

IBM Big Data Hub

DECEMBER 20, 2023

An AI strategy allows organizations to purposefully harness AI capabilities and align AI initiatives with overall business objectives. Define clear objectives What problems does the organization need to solve? Algorithms: Algorithms are the rules or instructions that enable machines to learn, analyze data and make decisions.

Strategy 71

Strategy Business Objectives Cost-Benefit Consulting 71

Ontotext

FEBRUARY 12, 2024

This is especially beneficial when teams need to increase data product velocity with trust and data quality, reduce communication costs, and help data solutions align with business objectives. In most enterprises, data is needed and produced by many business units but owned and trusted by no one.

Data-driven 59

Data-driven Data Lake Data Quality Business Objectives 59

AWS Big Data

AUGUST 1, 2024

Migrating to Amazon Redshift offers organizations the potential for improved price-performance, enhanced data processing, faster query response times, and better integration with technologies such as machine learning (ML) and artificial intelligence (AI).

Data Warehouse 114

Data Warehouse KPI Optimization Cost-Benefit 114

IBM Big Data Hub

JUNE 30, 2022

The rise of data strategy. There’s a renewed interest in reflecting on what can and should be done with data, how to accomplish those goals and how to check for data strategy alignment with business objectives. 5 recommendations for a data strategy in the new multi-everything landscape.

Data Strategy 56

Data Strategy Strategy Business Objectives Data-driven 56

AWS Big Data

MARCH 7, 2023

This post also discusses the art of the possible with newer innovations in AWS services around streaming, machine learning (ML), data sharing, and serverless capabilities. ETL (extract, transform, and load) technologies, streaming services, APIs, and data exchange interfaces are the core components of this pillar.

Analytics 97

Analytics Data Warehouse Data Lake Metadata 97

bridgei2i

JUNE 23, 2021

These include:lack of understanding of the business-centric use cases of AI, IT gaps,lack of skilled employees, issues in data quality, and resistance to incorporate new technologies into the framework. The accuracy of input data helps to maintain the output quality. Identify AI Use-Cases. Identify KPIs.

Consulting 52

Consulting Key Performance Indicator Business Objectives Data Strategy 52

IBM Big Data Hub

JULY 27, 2023

Trust and AI With access to the right data, it is easier to democratize AI for all users by using the power of foundation models to support a wide range of tasks. However, it’s important to factor in the opportunities and risks of foundation models—in particular, the trustworthiness of models to deploying AI at scale.

Management 54

Management Enterprise Modeling Data Quality 54

BizAcuity

APRIL 1, 2023

However, many businesses seem to face a lot of challenges, which includes ensuring a ‘single source of truth’ across the organization. Several large organizations have faltered on different stages of BI implementation, from poor data quality to the inability to scale due to larger volumes of data and extremely complex BI architecture.

Business Intelligence 52

Business Intelligence Consulting KPI Data Warehouse 52

BizAcuity

JANUARY 31, 2023

However, many businesses seem to face a lot of challenges, which includes ensuring a ‘single source of truth’ across the organization. Several large organizations have faltered on different stages of BI implementation, from poor data quality to the inability to scale due to larger volumes of data and extremely complex BI architecture.

Business Intelligence 52

Business Intelligence Consulting KPI Data Warehouse 52

Alation

MARCH 14, 2023

It should make data available, maintain data consistency and accuracy, and support data security. Gartner describes it as ‘ a highly dynamic process employed to support the acquisition, organisation, analysis, and delivery of data in support of business objectives ’. Why is a data strategy important?

Data Strategy 52

Data Strategy Strategy Metadata Data Quality 52

Ontotext

SEPTEMBER 1, 2023

Terms related to GenAI such as hallucinations and Large Language Models (LLMs) have become lingua-franca for any and every business conversation. Generative AI refers to computational models that are trained on massive amounts of text data and output in the form of text, images, video, audio, new data, and even code.

Risk 52

Risk Modeling Data Quality Data Governance 52

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.

Business Intelligence 52

Business Intelligence Software Data-driven Predictive Modeling 52

Ontotext

JULY 12, 2024

The automatic tagging specifically helps ensure consistency, which generates better data quality and deeper analytics and reporting. Among the main benefits of this bundle is the ability to manage all digital assets in one place, avoiding intensive data migrations.

Enterprise 59

Enterprise Cost-Benefit Metadata Data Integration 59

Ontotext

MAY 16, 2024

There is a confluence of activity – including generative AI models, digital twins, and shared ledger capabilities – that are having a profound impact on enterprises. This is designed to identify business priorities and must be aligned with the data from initial use cases.

Enterprise 52

Enterprise Data-driven Business Objectives Cost-Benefit 52

Alation

DECEMBER 15, 2021

Identifying, standardizing, and governing authoritative data sources. On the other hand, an offensive data strategy supports business objectives. Integrating customer and market data for planning future business goals. Build a Governance Model. A one-size-fits-all data governance model does not exist.

Data Governance 52

Data Governance Strategy Metadata Data Strategy 52

CIO Business Intelligence

FEBRUARY 20, 2023

This certification requires deep understanding of Salesforce features and functionality, as well as the ability to model a role hierarchy, data model, and appropriate sharing mechanisms. Salesforce Application Architect A Salesforce Certified Application Architect designs and develops custom solutions on the Salesforce platform.

B2B 87

B2B Consulting Sales Cost-Benefit 87

Alation

AUGUST 26, 2021

Business Intelligence (BI) is explanatory and backward-looking. These future-oriented models are used to make predictions. Today, modern organizations use AI to glean competitive insights, pulling nuggets of wisdom from a river of data. AI and ML are used in concert to predict possible events and model outcomes.

Metadata 64

Metadata Data Governance Dashboards Software 64

Cloudera

JANUARY 22, 2019

An organization needs a unified data management and analytics platform that can support its business objectives. Cloudera Enterprise is a one-stop shop for running analytics models and algorithms against multiple data sources across on-premises and cloud, and sometimes real-time data sources.

Big Data 44

Big Data Data Lake Internet of Things Enterprise 44

FineReport

APRIL 26, 2023

For example, a computer manufacturing company could develop new models or add features to products that are in high demand. E-commerce giants like Alibaba and Amazon extensively use big data to understand the market. How to Choose the Right Big Data Analytics Tools? It is scalable and secure to use. Easy implementation.

Big Data 52

Big Data Data Analytics Analytics Cost-Benefit 52

O'Reilly on Data

JULY 28, 2020

You must detect when the model has become stale, and retrain it as necessary. The Marketing team built the first model, but because it was from marketing, the model optimized for CTR and lead conversion. Data Exploration and Experimentation. Modeling and Evaluation.

Marketing 364

Marketing Experimentation Metrics Testing 364

CIO Business Intelligence

OCTOBER 2, 2024

An AI policy serves as a framework to ensure that AI systems align with ethical standards, legal requirements and business objectives. While this leads to efficiency, it also raises questions about transparency and data usage. This includes regular audits to guarantee data quality and security throughout the AI lifecycle.

Gap analysis 119

Gap analysis Risk Manufacturing Data Governance 119