CIO Business Intelligence

SEPTEMBER 15, 2023

From the CEO’s perspective, an optimized IT services portfolio maximizes cost efficiency, flexibility, and scalability. It enables the organization to focus on its core business while managing risks and accelerating time-to-market for new products and services.

Optimization 111

Optimization IT Metrics Marketing 111

AWS Big Data

NOVEMBER 17, 2023

Starting today, the Athena SQL engine uses a cost-based optimizer (CBO), a new feature that uses table and column statistics stored in the AWS Glue Data Catalog as part of the table’s metadata. Let’s discuss some of the cost-based optimization techniques that contributed to improved query performance.

Optimization 130

Optimization Statistics Metadata Data Lake 130

O'Reilly on Data

JUNE 15, 2023

Should we risk loss of control of our civilization?” The creators of generative AI systems and Large Language Models already have tools for monitoring, modifying, and optimizing them. And they are stress testing and “ red teaming ” them to uncover vulnerabilities. Some systems and use cases are riskier than others.

Metrics 289

Metrics Reporting Measurement Finance 289

IBM Big Data Hub

NOVEMBER 6, 2023

It’s at these endpoints that company and user data is vulnerable to various types of attacks and security risks, including: Authentication-based attacks : where hackers try to guess or steal user passwords or exploit weak authentication processes to gain access to API servers. Security testing.

Optimization 113

Optimization Testing Software Risk 113

CIO Business Intelligence

OCTOBER 8, 2024

You risk adding to the hype where there will be no observable value. The learning phase Two key grounding musts: Non-mission critical workloads and (public) data Internal/private (closed) exposure This ensures no corporate information or systems will be exposed to any form of risk. Test the customer waters.

Risk 124

Risk Technology Cost-Benefit Internet of Things 124

datapine

MAY 2, 2023

You can use big data analytics in logistics, for instance, to optimize routing, improve factory processes, and create razor-sharp efficiency across the entire supply chain. Your Chance: Want to test a professional logistics analytics software? A testament to the rising role of optimization in logistics.

Big Data 275

Big Data Internet of Things Cost-Benefit Optimization 275

Cloudera

JUNE 29, 2023

To ensure the stability of the US financial system, the implementation of advanced liquidity risk models and stress testing using (MI/AI) could potentially serve as a protective measure. To improve the way they model and manage risk, institutions must modernize their data management and data governance practices.

Data Architecture 91

Data Architecture Risk Management Risk Management 91

CIO Business Intelligence

JUNE 21, 2024

INE Security , a leading global cybersecurity training and cybersecurity certification provider, predicts large language model (LLM) applications like chatbots and AI-drive virtual assistants will be at particular risk. “AI Strategies to Optimize Teams for AI and Cybersecurity 1.

Optimization 122

Optimization Gap analysis Strategy Data-driven 122

DataKitchen

NOVEMBER 5, 2024

Data is typically organized into project-specific schemas optimized for business intelligence (BI) applications, advanced analytics, and machine learning. This involves setting up automated, column-by-column quality tests to quickly identify deviations from expected values and catch emerging issues before they impact downstream layers.

Data Quality 204

Data Quality Testing Metrics Reporting 204

IBM Big Data Hub

JANUARY 24, 2024

To mitigate and prepare for such risks, penetration testing is a necessary step in finding security vulnerabilities that an attacker might use. What is penetration testing? A penetration test , or “pen test,” is a security test that is run to mock a cyberattack in action.

Testing 72

Testing Risk Reporting IoT 72

DataKitchen

SEPTEMBER 20, 2021

The best way to ensure error-free execution of data production is through automated testing and monitoring. The DataKitchen Platform enables data teams to integrate testing and observability into data pipeline orchestrations. Automated tests work 24×7 to ensure that the results of each processing stage are accurate and correct.

Testing 246

Testing Metrics Measurement Dashboards 246

Rocket-Powered Data Science

JUNE 17, 2022

Explore and test-drive it (with a free trial) here. Reference ) Security information and event management (SIEM) on the Splunk platform is enhanced with end-to-end visibility and platform extensibility, with machine learning and automation (AIOps), with risk-based alerting, and with Federated Search (i.e., is here, now!

Machine Learning 238

Machine Learning Recreation/Entertainment Risk Business Objectives 238

Cloudera

DECEMBER 19, 2023

There, I met with IT leaders across multiple lines of business and agencies in the US Federal government focused on optimizing the value of AI in the public sector. AI can optimize citizen-centric service delivery by predicting demand and customizing service delivery, resulting in reduced costs and improved outcomes.

Optimization 96

Optimization Cost-Benefit Unstructured Data Risk 96

O'Reilly on Data

NOVEMBER 28, 2023

Unexpected outcomes, security, safety, fairness and bias, and privacy are the biggest risks for which adopters are testing. We’re not encouraging skepticism or fear, but companies should start AI products with a clear understanding of the risks, especially those risks that are specific to AI.

Enterprise 277

Enterprise Modeling Testing Reporting 277

IBM Big Data Hub

JANUARY 25, 2024

Many asset-intensive businesses are prioritizing inventory optimization due to the pressures of complying with growing industry 4.0 Over time, inventory managers have tested different approaches to determine the best fit for their organizations. regulations, undergoing digital transformation and the need for cost-cutting.

Optimization 73

Optimization Cost-Benefit Prescriptive Analytics Manufacturing 73

O'Reilly on Data

JUNE 19, 2019

In a previous post , we noted some key attributes that distinguish a machine learning project: Unlike traditional software where the goal is to meet a functional specification, in ML the goal is to optimize a metric. A catalog or a database that lists models, including when they were tested, trained, and deployed.

Modeling 195

Modeling Machine Learning Testing Metrics 195

O'Reilly on Data

SEPTEMBER 15, 2020

Technical competence results in reduced risk and uncertainty. AI initiatives may also require significant considerations for governance, compliance, ethics, cost, and risk. Likewise, AI doesn’t inherently optimize supply chains, detect diseases, drive cars, augment human intelligence, or tailor promotions to different market segments.

Advertising 299

Advertising Cost-Benefit ROI Machine Learning 299

IBM Big Data Hub

MARCH 6, 2024

The hybrid model allows organizations to gradually transition to the cloud, managing risks associated with a complete migration while benefiting from cloud scalability and flexibility. Re-platforming With a re-platforming migration, some adjustments or optimizations are made to the applications before moving them to the cloud.

Optimization 73

Optimization Strategy Cost-Benefit Testing 73

CIO Business Intelligence

AUGUST 16, 2023

But today, Svevia is driving cross-sector digitization projects where new technology for increased safety for road workers and users is tested. Since the route optimization came into place, fewer emptyings are required, he notes. A third area to be optimized is the salting of roads during the winter.

Risk 98

Risk Cost-Benefit Internet of Things Digital Transformation 98

IBM Big Data Hub

SEPTEMBER 12, 2023

The UK government’s Ecosystem of Trust is a potential future border model for frictionless trade, which the UK government committed to pilot testing from October 2022 to March 2023.

Testing 83

Testing Modeling Cost-Benefit Consulting 83

O'Reilly on Data

JUNE 7, 2022

We have a lot of vague notions about the Turing test, but in the final analysis, Turing wasn’t offering a definition of machine intelligence; he was probing the question of what human intelligence means. And granted, a lot can be done to optimize training (and DeepMind has done a lot of work on models that require less energy).

Modeling 363

Modeling Interactive Optimization Deep Learning 363

DataKitchen

NOVEMBER 27, 2024

Without contextual specificity, these dimensions risk becoming check-the-box exercises rather than actionable frameworks that help organizations identify and address the root causes of data quality issues. This approach allows enterprises to hold data suppliers accountable or optimize their ingestion processes to ensure higher data integrity.

Data Quality 219

Data Quality Dashboards Metrics Cost-Benefit 219

O'Reilly on Data

SEPTEMBER 19, 2023

You can see a simulation as a temporary, synthetic environment in which to test an idea. Millions of tests, across as many parameters as will fit on the hardware. “Here’s our risk model. A number of scholars have tested this shuffle-and-recombine-till-we-find-a-winner approach on timetable scheduling.

Machine Learning 253

Machine Learning Testing Modeling Cost-Benefit 253

Smart Data Collective

JULY 9, 2023

One benefit is that they can help with conversion rate optimization. Collecting Relevant Data for Conversion Rate Optimization Here is some vital data that e-commerce businesses need to collect to improve their conversion rates. One report found that global e-commerce brands spent over $16.7 billion on analytics last year.

Optimization 82

Optimization Data Analytics Analytics Data-driven 82

CIO Business Intelligence

DECEMBER 14, 2023

The timing for these advancements is optimal as the industry grapples with skilled labor shortages, supply chain challenges, and a highly competitive global marketplace. Process optimization In manufacturing, process optimization that maximizes quality, efficiency, and cost-savings is an ever-present goal.

Manufacturing 143

Manufacturing Cost-Benefit Unstructured Data Optimization 143

DataKitchen

SEPTEMBER 21, 2023

L1 is usually the raw, unprocessed data ingested directly from various sources; L2 is an intermediate layer featuring data that has undergone some form of transformation or cleaning; and L3 contains highly processed, optimized, and typically ready for analytics and decision-making processes.

Testing 182

Testing Data Quality Predictive Modeling Metrics 182

O'Reilly on Data

JULY 15, 2019

In recent posts, we described requisite foundational technologies needed to sustain machine learning practices within organizations, and specialized tools for model development, model governance, and model operations/testing/monitoring. Note that the emphasis of SR 11-7 is on risk management.). Sources of model risk.

Machine Learning 38

Machine Learning Management Enterprise Risk Management 38

CIO Business Intelligence

SEPTEMBER 26, 2024

One is the security and compliance risks inherent to GenAI. To make accurate, data-driven decisions, businesses need to feed LLMs with proprietary information, but this risks exposing sensitive data to unauthorized parties. That’s because significant challenges persist in leveraging GenAI’s large language models (LLMs).

Enterprise 130

Enterprise Data-driven Risk Testing 130

CIO Business Intelligence

DECEMBER 3, 2024

By classifying data based on its sensitivity and implementing access controls, organizations can prevent unauthorized access to confidential data, mitigating the risk of breaches or misuse of genAI applications. Data optimization. Start your free test drive of BlueXP classification in a completely isolated environment.

Data Governance 114

Data Governance Snapshot Machine Learning Risk 114

DataKitchen

NOVEMBER 18, 2021

The data analytics lifecycle is a factory, and like other factories, it can be optimized with techniques borrowed from methods like lean manufacturing. Write tests that catch data errors. To avoid errors and outages, fearful engineers give each analytics project a more extended development and test schedule.

Testing 246

Testing Data Governance Measurement Software 246

DataKitchen

JANUARY 5, 2021

Tools influence their optimal iteration cycle time, e.g., months/weeks/days. Tools affect their risk tolerance. Observability – Testing inputs, outputs, and business logic at each stage of the data analytics pipeline. Tests catch potential errors and warnings before they are released, so the quality remains high.

Testing 147

Testing Data Governance Metadata Visualization 147

Smart Data Collective

DECEMBER 26, 2022

Before prioritizing your threats, risks, and remedies, determine the rules and regulations that your company is obliged to follow. Prioritize Your Risks and Assets. Once you are done with enlisting your threat vectors, it is important to go through a risk assessment and create a prioritization list of your assets.

Strategy 136

Strategy Testing Risk Software 136

O'Reilly on Data

MARCH 23, 2023

What is it, how does it work, what can it do, and what are the risks of using it? Many of these go slightly (but not very far) beyond your initial expectations: you can ask it to generate a list of terms for search engine optimization, you can ask it to generate a reading list on topics that you’re interested in.

IT 267

IT Modeling Testing Risk 267

O'Reilly on Data

MAY 14, 2020

Because they are building an AI product that will be consumed by the masses, it’s possible (perhaps even desirable) to optimize for rapid experimentation and iteration over accuracy—especially at the beginning of the product cycle. a deep understanding of A/B testing , and a similarly deep knowledge of model evaluation techniques.

Management 363

Management Experimentation B2B Machine Learning 363

CIO Business Intelligence

APRIL 12, 2024

Large banking firms are quietly testing AI tools under code names such as as Socrates that could one day make the need to hire thousands of college graduates at these firms obsolete, according to the report. But that’s just the tip of the iceberg for a future of AI organizational disruptions that remain to be seen, according to the firm.

Experimentation 143

Experimentation Reporting Testing Statistics 143

CIO Business Intelligence

DECEMBER 3, 2024

But supporting a technology strategy that attempts to offset skills gaps by supplanting the need for those skills is also changing the fabric of IT careers — and the long-term prospects of those at risk of being automated out of work. In software development today, automated testing is already well established and accelerating.

IT 128

IT Testing Software Data-driven 128

CIO Business Intelligence

APRIL 21, 2022

Combining Agile and DevOps with elements such as cloud, testing, security, risk management and compliance creates a modernized technology delivery approach that can help an organization achieve greater speed, reduced risk, and enhanced quality and experience. All hands on deck .

Digital Transformation 145

Digital Transformation Key Performance Indicator Risk Testing 145