CIO Business Intelligence

NOVEMBER 4, 2024

Companies are seeking ways to enhance reporting, meet regulatory requirements, and optimize IT operations. Data security, data quality, and data governance still raise warning bells Data security remains a top concern. AI applications rely heavily on secure data, models, and infrastructure.

Marketing 128

Marketing Data Quality Data Governance Digital Transformation 128

Smart Data Collective

APRIL 20, 2022

Companies that utilize data analytics to make the most of their business model will have an easier time succeeding with Amazon. One of the best ways to create a profitable business model with Amazon involves using data analytics to optimize your PPC marketing strategy. However, it is important to make sure the data is reliable.

Data Quality 128

Data Quality Analytics Testing Sales 128

AWS Big Data

AUGUST 8, 2024

They establish data quality rules to ensure the extracted data is of high quality for accurate business decisions. These rules commonly assess the data based on fixed criteria reflecting the current business state. In this post, we demonstrate how this feature works with an example.

Data Quality 113

Data Quality Statistics Visualization Metrics 113

DataKitchen

JULY 12, 2023

The Syntax, Semantics, and Pragmatics Gap in Data Quality Validate Testing Data Teams often have too many things on their ‘to-do’ list. Each unit will have unique data sets with specific data quality test requirements.

Data Quality 130

Data Quality Testing Manufacturing Finance 130

AWS Big Data

JUNE 6, 2023

We are excited to announce the General Availability of AWS Glue Data Quality. Our journey started by working backward from our customers who create, manage, and operate data lakes and data warehouses for analytics and machine learning. It takes days for data engineers to identify and implement data quality rules.

Data Quality 98

Data Quality Statistics Data Lake Visualization 98

AWS Big Data

MAY 23, 2024

They establish data quality rules to ensure the extracted data is of high quality for accurate business decisions. These rules assess the data based on fixed criteria reflecting current business states. We are excited to talk about how to use dynamic rules , a new capability of AWS Glue Data Quality.

Data Quality 103

Data Quality Metrics Data Lake Sales 103

AWS Big Data

MARCH 12, 2024

In recent years, data lakes have become a mainstream architecture, and data quality validation is a critical factor to improve the reusability and consistency of the data. In this post, we provide benchmark results of running increasingly complex data quality rulesets over a predefined test dataset.

Data Quality 105

Data Quality Measurement Testing Visualization 105

David Menninger's Analyst Perspectives

NOVEMBER 5, 2024

For example, many tasks in the accounting close follow iterative paths involving multiple participants, as do supply chain management events where a delivery delay can set up a complex choreography of collaborative decision-making to deal with the delay, preferably in a relatively optimal fashion.

Optimization 130

Optimization Machine Learning Software Interactive 130

AWS Big Data

JUNE 6, 2023

Alerts and notifications play a crucial role in maintaining data quality because they facilitate prompt and efficient responses to any data quality issues that may arise within a dataset. This proactive approach helps mitigate the risk of making decisions based on inaccurate information.

Data Quality 83

Data Quality Metrics Data-driven Visualization 83

CIO Business Intelligence

JANUARY 5, 2025

Research from Gartner, for example, shows that approximately 30% of generative AI (GenAI) will not make it past the proof-of-concept phase by the end of 2025, due to factors including poor data quality, inadequate risk controls, and escalating costs. [1] Reliability and security is paramount.

Enterprise 124

Enterprise Cost-Benefit Unstructured Data Data Quality 124

DataKitchen

APRIL 13, 2021

RightData – A self-service suite of applications that help you achieve Data Quality Assurance, Data Integrity Audit and Continuous Data Quality Control with automated validation and reconciliation capabilities. QuerySurge – Continuously detect data issues in your delivery pipelines. Data breaks.

Testing 300

Testing Machine Learning Consulting Data Science 300

CIO Business Intelligence

APRIL 8, 2025

As technology and business leaders, your strategic initiatives, from AI-powered decision-making to predictive insights and personalized experiences, are all fueled by data. Yet, despite growing investments in advanced analytics and AI, organizations continue to grapple with a persistent and often underestimated challenge: poor data quality.

Data Quality 59

Data Quality Data-driven Key Performance Indicator Metadata 59

CIO Business Intelligence

MARCH 25, 2025

Data debt that undermines decision-making In Digital Trailblazer , I share a story of a private company that reported a profitable year to the board, only to return after the holiday to find that data quality issues and calculation mistakes turned it into an unprofitable one.

Risk 140

Risk Cost-Benefit Data-driven Digital Transformation 140

O'Reilly on Data

JUNE 18, 2019

As model building become easier, the problem of high-quality data becomes more evident than ever. Even with advances in building robust models, the reality is that noisy data and incomplete data remain the biggest hurdles to effective end-to-end solutions. Data integration and cleaning. Data programming.

Machine Learning 279

Machine Learning Data Quality Statistics Modeling 279

CIO Business Intelligence

NOVEMBER 13, 2024

The company has already rolled out a gen AI assistant and is also looking to use AI and LLMs to optimize every process. One is going through the big areas where we have operational services and look at every process to be optimized using artificial intelligence and large language models. We’re doing two things,” he says.

IT 141

IT Consulting ROI Cost-Benefit 141

CIO Business Intelligence

NOVEMBER 19, 2024

They are often unable to handle large, diverse data sets from multiple sources. Another issue is ensuring data quality through cleansing processes to remove errors and standardize formats. Staffing teams with skilled data scientists and AI specialists is difficult, given the severe global shortage of talent.

Analytics 97

Analytics Cost-Benefit Finance Data-driven 97

O'Reilly on Data

NOVEMBER 19, 2024

decomposes a complex task into a graph of subtasks, then uses LLMs to answer the subtasks while optimizing for costs across the graph. A generalized, unbundled workflow A more accountable approach to GraphRAG is to unbundle the process of knowledge graph construction, paying special attention to data quality.

Unstructured Data 318

Unstructured Data Structured Data Statistics Modeling 318

AWS Big Data

JUNE 6, 2023

Data consumers lose trust in data if it isn’t accurate and recent, making data quality essential for undertaking optimal and correct decisions. Evaluation of the accuracy and freshness of data is a common task for engineers. Currently, various tools are available to evaluate data quality.

Data Quality 84

Data Quality Data-driven Data Lake Metrics 84

CIO Business Intelligence

JANUARY 1, 2025

It allows tourism companies to anticipate demand, optimize resource management, and improve sustainability, he says.And in an environment where speed, precision, and personalization are essential, its vital to adopt solutions to improve the customer experience and be on the front foot to new market changes.

Strategy 115

Strategy Digital Transformation Optimization Technology 115

Smarten

APRIL 25, 2024

How Can I Ensure Data Quality and Gain Data Insight Using Augmented Analytics? There are many business issues surrounding the use of data to make decisions. One such issue is the inability of an organization to gather and analyze data.

Data Quality 64

Data Quality Analytics Machine Learning Visualization 64

AWS Big Data

NOVEMBER 22, 2024

For example, instead of processing an entire dataset daily, dbt can be configured to transform only the data ingested in the last 24 hours, making data operations more efficient and cost-effective. Cost management and optimization – Because Athena charges based on the amount of data scanned by each query, cost optimization is critical.

Data Lake 86

Data Lake Data Warehouse Cost-Benefit Data Transformation 86

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 Consider these questions: Do you have a platform that combines statistical analyses, prescriptive analytics and optimization algorithms? The post MRO spare parts optimization appeared first on IBM Blog.

Optimization 73

Optimization Cost-Benefit Prescriptive Analytics Manufacturing 73

Cloudera

JULY 15, 2021

The regulatory oversight coupled with potential AI applications launched a discussion about the quality of the data – the classic “garbage-in, garbage-out” challenge. This was not challenged, but the firms participating are in various states of adoption on data usage and governance.

Risk 100

Risk Optimization Management Insurance 100

CIO Business Intelligence

FEBRUARY 6, 2025

Imagine generating complex narratives from data visualizations or using conversational BI tools that respond to your queries in real time. In retail, they can personalize recommendations and optimize marketing campaigns. Sustainable IT is about optimizing resource use, minimizing waste and choosing the right-sized solution.

Unstructured Data 115

Unstructured Data Manufacturing Data Governance Sales 115

datapine

JANUARY 21, 2020

Operational optimization and forecasting. Cost optimization. Another important factor to consider is cost optimization. Enhanced data quality. One of the most clear-cut and powerful benefits of data intelligence for business is the fact that it empowers the user to squeeze every last drop of value from their data.

Business Intelligence 259

Business Intelligence Reporting Cost-Benefit Dashboards 259

AWS Big Data

SEPTEMBER 11, 2024

This also includes building an industry standard integrated data repository as a single source of truth, operational reporting through real time metrics, data quality monitoring, 24/7 helpdesk, and revenue forecasting through financial projections and supply availability projections.

Data Architecture 98

Data Architecture Optimization Data Warehouse Metadata 98

O'Reilly on Data

JULY 28, 2020

If this sounds fanciful, it’s not hard to find AI systems that took inappropriate actions because they optimized a poorly thought-out metric. CTRs are easy to measure, but if you build a system designed to optimize these kinds of metrics, you might find that the system sacrifices actual usefulness and user satisfaction.

Marketing 364

Marketing Experimentation Metrics Testing 364

AWS Big Data

DECEMBER 4, 2024

These formats, exemplified by Apache Iceberg, Apache Hudi, and Delta Lake, addresses persistent challenges in traditional data lake structures by offering an advanced combination of flexibility, performance, and governance capabilities. The AWS Glue Data Catalog addresses these challenges through its managed storage optimization feature.

Snapshot 84

Snapshot Metadata Data Lake Optimization 84

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? Who are they?

IT 317

IT Statistics KPI Data-driven 317

Cloudera

NOVEMBER 13, 2024

This guarantees data quality and automates the laborious, manual processes required to maintain data reliability. Robust Data Catalog: Organizations can create company-wide consistency with a self-creating, self-updating data catalog.

Metadata 90

Metadata Management Data Governance Data-driven 90

AWS Big Data

JULY 13, 2023

Data quality for account and customer data – Altron wanted to enable data quality and data governance best practices. Goals – Lay the foundation for a data platform that can be used in the future by internal and external stakeholders.

Optimization 96

Optimization B2B Data Quality Sales 96

DataKitchen

AUGUST 16, 2024

At DataKitchen, we think of this is a ‘meta-orchestration’ of the code and tools acting upon the data. Data Pipeline Observability: Optimizes pipelines by monitoring data quality, detecting issues, tracing data lineage, and identifying anomalies using live and historical metadata.

Marketing 124

Marketing Data Quality Testing Metadata 124

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. Quality depends not just on code, but also on data, tuning, regular updates, and retraining.

Modeling 257

Modeling Machine Learning Testing Metrics 257

AWS Big Data

APRIL 8, 2025

We will explore Icebergs concurrency model, examine common conflict scenarios, and provide practical implementation patterns of both automatic retry mechanisms and situations requiring custom conflict resolution logic for building resilient data pipelines.

Snapshot 94

Snapshot Management Metadata Big Data 94

O'Reilly on Data

JULY 15, 2019

Regulators behind SR 11-7 also emphasize the importance of data—specifically data quality , relevance , and documentation. While models garner the most press coverage, the reality is that data remains the main bottleneck in most ML projects.

Machine Learning 52

Machine Learning Management Enterprise Risk Management 52

CIO Business Intelligence

OCTOBER 31, 2024

BPM as a driver of IT success Making a significant contribution to Norma’s digital transformation, a BPM team was initiated in 2020 and its managers support all business areas to improve and harmonize the understanding of applications and processes, as well as data quality.

IT 89

IT Digital Transformation Machine Learning Data Quality 89

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. What is Data in Use?

Testing 169

Testing Data Quality Predictive Modeling Metrics 169