AWS Big Data

JANUARY 15, 2025

By integrating various data producers and connecting them to data consumers such as Amazon SageMaker and Tableau, Amazon DataZone functions as a digital library to streamline data sharing and integration across EUROGATEs operations.

IoT 111

IoT Machine Learning Metadata Data-driven 111

O'Reilly on Data

OCTOBER 19, 2021

Feature stores aim to solve the challenge that many data scientists in an organization require similar data transformations and features for their work and labeling solutions deal with the very real challenges associated with hand labeling datasets. The iteration cycles should be measured in hours or days, not in months.

IT 364

IT Testing Experimentation Software 364

DataKitchen

OCTOBER 5, 2021

Clear measurement and monitoring of results. DataOps establishes a process hub that automates data production and analytics development workflows so that the data team is more efficient, innovative and less prone to error. The data engineer builds data transformations. Their product is the data.

Testing 154

Testing Dashboards Measurement Experimentation 154

CIO Business Intelligence

JULY 5, 2022

Business analytics can help you improve operational efficiency, better understand your customers, project future outcomes, glean insights to aid in decision-making, measure performance, drive growth, discover hidden trends, generate leads, and scale your business in the right direction, according to digital skills training company Simplilearn.

Business Analytics 136

Business Analytics Prescriptive Analytics Data mining Diagnostic Analytics 136

CIO Business Intelligence

JANUARY 12, 2023

Data provides insights that support the overall strategy of the university. It can also help with specific use cases: from understanding where to invest resources and discovering new ways to engage pupils, to measuring academic outcomes and boosting student performance. Comprehensive upskilling programme to overcome data skills gaps.

Data Strategy 98

Data Strategy Strategy IT Consulting 98

CIO Business Intelligence

JUNE 23, 2022

In the data supply chain, there are a variety of sources of internal and external data (from data brokers, social media/sentiment analysis, etc.) and just like a physical supply chain, reducing complexity in the data supply chain helps improve overall quality. How can reducing complexity improve the quality?

Data Quality 98

Data Quality Key Performance Indicator Metrics KPI 98

CIO Business Intelligence

DECEMBER 22, 2022

According to the DataOps Manifesto , DataOps teams value analytics that work, measuring the performance of data analytics by the insights they deliver. Analytics, Collaboration Software, Data Management, Data Mining, Data Science, IT Strategy, Small and Medium Business.

Analytics 130

Analytics Machine Learning Data mining Software 130

David Menninger's Analyst Perspectives

NOVEMBER 7, 2024

The difference is in using advanced modeling and data management to make faster scenario planning possible, driven by actionable key performance measures that enable faster, well-informed decision cycles. This may sound like FP&A’s mission today.

Forecasting 130

Forecasting Machine Learning Finance Predictive Analytics 130

CIO Business Intelligence

JUNE 13, 2022

“I thought I was hired for digital transformation but what is really needed is a data transformation,” she says. To get there, Angel-Johnson has embarked on a master data management initiative.

IT 144

IT Digital Transformation Internet of Things Strategy 144

CIO Business Intelligence

JUNE 7, 2022

Data analytics draws from a range of disciplines — including computer programming, mathematics, and statistics — to perform analysis on data in an effort to describe, predict, and improve performance. What are the four types of data analytics?

Data Analytics 135

Data Analytics Diagnostic Analytics Management Analytics 135

AWS Big Data

AUGUST 1, 2024

However, you might face significant challenges when planning for a large-scale data warehouse migration. This includes the ETL processes that capture source data, the functional refinement and creation of data products, the aggregation for business metrics, and the consumption from analytics, business intelligence (BI), and ML.

Data Warehouse 115

Data Warehouse KPI Optimization Cost-Benefit 115

AWS Big Data

AUGUST 9, 2023

The advent of rapid adoption of serverless data lake architectures—with ever-growing datasets that need to be ingested from a variety of sources, followed by complex data transformation and machine learning (ML) pipelines—can present a challenge.

Data Lake 98

Data Lake Metrics Cost-Benefit Testing 98

Wayne Yaddow

MARCH 3, 2025

When implementing automated validation, AI-driven regression testing, real-time canary pipelines, synthetic data generation, freshness enforcement, KPI tracking, and CI/CD automation, organizations can shift from reactive data observability to proactive data quality assurance.

Data Quality 52

Data Quality Strategy ROI Testing 52

AWS Big Data

SEPTEMBER 5, 2024

If storing operational data in a data warehouse is a requirement, synchronization of tables between operational data stores and Amazon Redshift tables is supported. In scenarios where data transformation is required, you can use Redshift stored procedures to modify data in Redshift tables.

IoT 111

IoT Data Warehouse Cost-Benefit Reporting 111

AWS Big Data

MAY 3, 2023

As companies continue to expand their digital footprint, the importance of real-time data processing and analysis cannot be overstated. The ability to quickly measure and draw insights from data is critical in today’s business landscape, where rapid decision-making is key. Loader – This is where users specify a target database.

IoT 111

IoT Internet of Things Data Transformation Management 111

IBM Big Data Hub

JANUARY 9, 2024

Currently, no standardized process exists for overcoming data ingestion’s challenges, but the model’s accuracy depends on it. Increased variance: Variance measures consistency. Insufficient data can lead to varying answers over time, or misleading outliers, particularly impacting smaller data sets.

Enterprise 71

Enterprise Data Integration Data Quality Contextual Data 71

AWS Big Data

OCTOBER 11, 2023

Traditionally, such a legacy call center analytics platform would be built on a relational database that stores data from streaming sources. Data transformations through stored procedures and use of materialized views to curate datasets and generate insights is a known pattern with relational databases.

Management 131

Management Metadata Analytics Dashboards 131

IBM Big Data Hub

FEBRUARY 9, 2023

In our last blog , we delved into the seven most prevalent data challenges that can be addressed with effective data governance. Today we will share our approach to developing a data governance program to drive data transformation and fuel a data-driven culture. Don’t try to do everything at once!

Data Governance 76

Data Governance Business Objectives Data Quality Measurement 76

CIO Business Intelligence

JANUARY 9, 2023

To fuel self-service analytics and provide the real-time information customers and internal stakeholders need to meet customers’ shipping requirements, the Richmond, VA-based company, which operates a fleet of more than 8,500 tractors and 34,000 trailers, has embarked on a data transformation journey to improve data integration and data management.

Data Strategy 111

Data Strategy Strategy Data Governance Marketing 111

DataKitchen

DECEMBER 9, 2022

DataOps observability involves the use of various tools and techniques to monitor the performance of data pipelines, data lakes, and other data-related infrastructure. This can include tools for tracking the flow of data through pipelines, and for measuring the performance of data-related systems and processes.

Machine Learning 130

Machine Learning Data-driven Optimization Data Analytics 130

Sisense

AUGUST 6, 2020

This is also an important takeaway for teams seeking to implement AI successfully: Start with the key performance indicators (KPIs) you want to measure your AI app’s success with, and see where that dovetails with your expert domain knowledge. Then tailor your approach to leverage your unique data and expertise to excel in those KPI areas.

Management 95

Management Machine Learning Key Performance Indicator Cost-Benefit 95

Cloudera

OCTOBER 8, 2024

Detailed Data and Model Lineage Tracking*: Ensures comprehensive tracking and documentation of data transformations and model lifecycle events, enhancing reproducibility and auditability.

Optimization 75

Optimization Metrics Experimentation Enterprise 75

Anmut

MARCH 24, 2022

We could give many answers, but they all centre on the same root cause: most data leaders focus on flashy technology and symptomatic fixes instead of approaching data transformation in a way that addresses the root causes of data problems and leads to tangible results and business success. It doesn’t have to be this way.

ROI 52

ROI Measurement Data-driven Data Transformation 52

FineReport

JUNE 7, 2024

Elevate your data transformation journey with Dataiku’s comprehensive suite of solutions. Real-time Analytics : Tableau enables real-time analytics, providing instant insights into changing data trends and patterns.

Visualization 52

Visualization Predictive Analytics Dashboards Predictive Modeling 52

Domino Data Lab

AUGUST 20, 2019

While it has limitations, BMI is quickly calculated from body weight and height and serves as a surrogate for a characteristic that is very hard to accurately measure: proportion of lean body mass. Drop a column from a table—either based on a principled argument (we know the two columns are measuring the same thing) or based on a randomness.

Testing 68

Testing Modeling Interactive Measurement 68

AWS Big Data

NOVEMBER 13, 2023

In pursuit of this principle, strategic measures were undertaken to ensure a smooth migration process towards enabling data sharing, which included the following steps: Planning: Replicating users and groups to the consumer, to mitigate potential access complications for analytics, data science, and BI teams.

Data Warehouse 111

Data Warehouse Analytics Data Lake Data Science 111

CDW Research Hub

JANUARY 22, 2020

While the looming threat of hackers and security breaches should not be taken lightly, the good news is companies can mitigate risks commonly associated with breaches and safely migrate their database(s) to the cloud with proper planning, insight and preventive measures. So how do you keep your business out of the security breach headlines?

Measurement 52

Measurement Consulting Finance Risk 52

DataRobot Blog

APRIL 4, 2022

MMM stands for Marketing Mix Model and it is one of the oldest and most well-established techniques to measure the sales impact of marketing activity statistically. Data Requirements. As with any type of statistical model, data is key and GIGO (“Garbage In, Garbage Out”) principle definitely applies. What cannot be measured?

Machine Learning 52

Machine Learning Sales Measurement ROI 52

Sisense

OCTOBER 15, 2020

Note that during this entire process, the user didn’t need to define anything except data transformations: The processing job is automatically orchestrated, and exactly-once data consistency is guaranteed by the engine. Now, it’s time to build the dashboard and explore your data. Feel free to explore your data now.

Dashboards 98

Dashboards IoT Optimization Internet of Things 98

AWS Big Data

MAY 25, 2023

Data transformation plays a pivotal role in providing the necessary data insights for businesses in any organization, small and large. To gain these insights, customers often perform ETL (extract, transform, and load) jobs from their source systems and output an enriched dataset.

Reporting 96

Reporting Metrics Optimization Data Lake 96

Jet Global

MAY 28, 2019

A data warehouse is typically used by companies with a high level of data diversity or analytical requirements.

Data Warehouse 85

Data Warehouse Reporting Business Intelligence Sales 85

AWS Big Data

MAY 16, 2023

Data collection and processing are handled by a third-party smart sensor manufacturer application residing in Amazon Virtual Private Cloud (Amazon VPC) private subnets behind a Network Load Balancer. The AWS Glue Data Catalog contains the table definitions for the smart sensor data sources stored in the S3 buckets.

Dashboards 98

Dashboards Statistics Data Collection Business Intelligence 98

Alation

NOVEMBER 22, 2022

Data governance is the foundation for these strategies. To unlock your data’s value, you need a data governance program that addresses: Data ownership. Data breach mitigation measures. Transparency over data usage. You follow the data. Efficient Access To Data. Data usage.

Data Governance 52

Data Governance Metadata Data-driven Unstructured Data 52

IBM Big Data Hub

OCTOBER 16, 2023

Getting started with foundation models An AI development studio can train, validate, tune and deploy foundation models and build AI applications quickly, requiring only a fraction of the data previously needed. Such datasets are measured by how many “tokens” (words or word parts) they include.

Risk 70

Risk Modeling Management Metadata 70

Alation

JANUARY 17, 2023

These help data analysts visualize key insights that can help you make better data-backed decisions. ELT Data Transformation Tools: ELT data transformation tools are used to extract, load, and transform your data. Examples of data transformation tools include dbt and dataform.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Science Data Transformation 52

erwin

JANUARY 11, 2019

Organizations have spent a lot of time and money trying to harmonize data across diverse platforms , including cleansing, uploading metadata, converting code, defining business glossaries, tracking data transformations and so on.

Data Governance 40

Data Governance Risk Metadata Management 40

Alation

OCTOBER 28, 2021

The CDO acts as a point-of-contact within the organization for data managers maintaining the daily activities. Monitor, Measure, and Continuously Improve. If your goal was to increase patients’ telehealth services usage, for example, you’ll need benchmarks of current usage to measure change with time.

Data Governance 52

Data Governance Measurement Data Quality Metrics 52