CIO Business Intelligence

JUNE 23, 2022

The challenge is to capture source of the data correctly from the outset and ensure data quality does not degrade when moving across the data supply-chain. A key supply chain management metric used to evaluate the performance of physical supply chains is OTIF – On-Time-In-Full. Supply chain complexity.

Data Quality 97

Data Quality Key Performance Indicator Metrics KPI 97

Sisense

AUGUST 6, 2020

AI can add value to your product/service in many ways, including: Improved business performance Reduced costs Increased customer satisfaction Improved brand value Risk reduction (reduced human error, fraud reduction, spam reduction) Improved convenience and accessibility of products. An obvious mechanical answer is: use relevance as a metric.

Management 95

Management Machine Learning Key Performance Indicator Cost-Benefit 95

O'Reilly on Data

JANUARY 17, 2023

In the past they understood the APIs of TensorFlow and Torch to build models by hand; today they are fluent in the autoML vendor’s APIs to train models, and they understand how to review the metrics. That is: what model risk does the company face?) It does not exist in the code. AutoML drives this point home.

Machine Learning 326

Machine Learning Predictive Modeling Software Modeling 326

DataKitchen

OCTOBER 25, 2022

When considering how organizations handle serious risk, you could look to NASA. The space agency created and still uses “mission control” where many screens share detailed data about all aspects of a space flight. Any data operation, regardless of size, complexity, or degree of risk, can benefit from DataOps Observability.

Testing 130

Testing Data-driven Visualization Dashboards 130

Alation

OCTOBER 28, 2021

Leaders are asking how they might use data to drive smarter decision making to support this new model and improve medical treatments that lead to better outcomes. Yet this is not without risks. To make good on this potential, healthcare organizations need to understand their data and how they can use it.

Data Governance 52

Data Governance Measurement Metrics Data Quality 52

AWS Big Data

JULY 20, 2023

Orca Security is an industry-leading Cloud Security Platform that identifies, prioritizes, and remediates security risks and compliance issues across your AWS Cloud estate. This ensures that the data is suitable for training purposes. Additionally, SageMaker training jobs are employed for training the models.

Data Lake 89

Data Lake Analytics Snapshot Optimization 89

AWS Big Data

FEBRUARY 21, 2023

We use Apache Spark as our main data processing engine and have over 1,000 Spark applications running over massive amounts of data every day. These Spark applications implement our business logic ranging from data transformation, machine learning (ML) model inference, to operational tasks. Their costs were climbing.

Cost-Benefit 55

Cost-Benefit Informatics Optimization Management 55

AWS Big Data

SEPTEMBER 19, 2023

Chime’s Risk Analysis team constantly monitors trends in our data to find patterns that indicate fraudulent transactions. However, with a minimum data freshness of 10 minutes, this architecture inherently didn’t align with the near real-time fraud detection use case.

Analytics 80

Analytics Risk Big Data Machine Learning 80

Alation

NOVEMBER 22, 2022

An active data governance framework includes: Assigning data stewards. Standardizing data formats. Identifying structured and unstructured data. Setting data management policies, like tagging data. Quantifying effectiveness with metrics. Balance Defensive And Offensive Data Strategy.

Data Governance 52

Data Governance Metadata Data-driven Unstructured Data 52

AWS Big Data

DECEMBER 21, 2023

The data products from the Business Vault and Data Mart stages are now available for consumers. smava decided to use Tableau for business intelligence, data visualization, and further analytics. The data transformations are managed with dbt to simplify the workflow governance and team collaboration.

Data Lake 90

Data Lake Data Warehouse Data-driven B2B 90

Jet Global

MAY 28, 2019

A data warehouse is typically used by companies with a high level of data diversity or analytical requirements. The only downside about a data warehouse is that, historically, it has a reputation for being complex, time-consuming, and expensive to build and maintain. Enhancing a Data Warehouse with Cubes. Download Now.

Data Warehouse 85

Data Warehouse Reporting Business Intelligence Sales 85

Jet Global

MAY 1, 2023

As a result, end users can better view shared metrics (backed by accurate data), which ultimately drives performance. CFO Priorities Manage expenses and cash flow Enable profitable growth Contain risk Plan for the future Connect the Dots Do the math. Present your business case. These might be the user stories you construct.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52

Jet Global

MAY 9, 2024

Data Extraction : The process of gathering data from disparate sources, each of which may have its own schema defining the structure and format of the data and making it available for processing. This can include tasks such as data ingestion, cleansing, filtering, aggregation, or standardization.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52