DataRobot Blog

MARCH 16, 2023

However, we’re now taking the information managed by DataRobot (such as the data , features , models , predictions ) and leveraging the capabilities of the Azure OpenAI Service to make it more accessible and understandable. An example of this is proposing why a feature has a high impact on predictions.

Data Science 98

Data Science Technology Data-driven Modeling 98

AWS Big Data

APRIL 3, 2024

For many enterprises and large organizations, it is not feasible to have one processing engine or tool to deal with the various business requirements. Apache Iceberg is an open-source table format that provides reliability, simplicity, and high performance for large datasets with transactional integrity between various processing engines.

Data Lake 93

Data Lake Snapshot Metadata Data Architecture 93

AWS Big Data

MARCH 25, 2024

Another example is an AI-driven observability and monitoring solution where FMs monitor real-time internal metrics of a system and produces alerts. For example, in a chatbot, data events could pertain to an inventory of flights and hotels or price changes that are constantly ingested to a streaming storage engine.

Data Lake 88

Data Lake Unstructured Data Management Modeling 88

AWS Big Data

OCTOBER 11, 2023

The lift and shift migration approach is limited in its ability to transform businesses because it relies on outdated, legacy technologies and architectures that limit flexibility and slow down productivity. This may require frequent truncation in certain tables to retain only the latest stream of events.

Management 103

Management Metadata Analytics Dashboards 103

Ontotext

MARCH 13, 2024

Our goal is to generate a knowledge space where information is easy to find, reuse, and fuel knowledge-driven insights. It also allows us to put the new features of our products into a real-world use case right away. Working in a cross-functional team also enables us to do short value-driven iterative cycles. What is OTKG?

Marketing 72

Marketing Knowledge Discovery Metadata Data-driven 72

AWS Big Data

DECEMBER 8, 2023

To achieve a data sharing architecture, the plan was to first spin up consumer clusters for development and testing environments for their data engineers that were moving key legacy code to dbt. They also wanted to ensure that they had adequate compute to run many jobs concurrently.

Data Warehouse 67

Data Warehouse Cost-Benefit KPI Risk 67

AWS Big Data

JANUARY 24, 2023

Serverless applications are a modernized way to perform analytics among business departments and engineering teams. Event-driven model Event-driven applications are increasingly popular among customers. Analytical reporting web applications can be implemented through an event-driven model.

Analytics 58

Analytics Data-driven Management Reporting 58

AWS Big Data

MARCH 19, 2024

For data engineering workloads when AWS Glue is used in such a constrained network configuration, your team may sometimes face hurdles running many jobs simultaneously. The following are some best practices to optimize AWS Glue IP address consumption: Right-sizing the job’s DPUs – AWS Glue is a distributed processing engine.

Optimization 86

Optimization Data-driven Management Testing 86

DataRobot Blog

FEBRUARY 28, 2023

The DataRobot AI Platform and the Snowflake Data Cloud provide an interoperable, scalable AI/ML solution and unique services that integrate with diverse ecosystems so that data-driven enterprises can focus on delivering trusted and impactful results. launch event on March 16th. Register here to be part of this virtual event.

Data Processing 72

Data Processing Experimentation Machine Learning Modeling 72

AWS Big Data

MARCH 14, 2024

Serving as a distributed log system, Kafka efficiently captures and stores diverse logs, from HTTP server access logs to security event audit logs. Kafka’s robust debugging features and administrative commands play a pivotal role in ensuring smooth operations and infrastructure health. We hadn’t updated Kafka version 2.0.0

Management 106

Management Insurance Optimization Strategy 106

AWS Big Data

MARCH 20, 2023

The two main approaches organizations employ to increase revenue are to expand geographically to enter new markets and to increase market share within a market by improving customer experience (CX). Poshmark engineers worked closely with AWS architects through the AWS Data Lab program.

Analytics 52

Analytics Slice and Dice Data Processing Data Lake 52

AWS Big Data

JULY 25, 2023

Alcion, a security-first, AI-driven backup-as-a-service (BaaS) platform, helps Microsoft 365 administrators quickly and intuitively protect data from cyber threats and accidental data loss. The team at Alcion used several features of OpenSearch Service managed domains to improve their operational stance. OpenSearch is an Apache-2.0-licensed,

Cost-Benefit 72

Cost-Benefit Modeling Management Optimization 72

AWS Big Data

APRIL 10, 2024

When data is used to improve customer experiences and drive innovation, it can lead to business growth,” – Swami Sivasubramanian , VP of Database, Analytics, and Machine Learning at AWS in With a zero-ETL approach, AWS is helping builders realize near-real-time analytics. For Engine type , select Amazon Aurora. Choose Save Changes.

Data Warehouse 90

Data Warehouse Analytics Metrics Snapshot 90

AWS Big Data

JANUARY 31, 2024

The massive volume of data is attributed to the encompassing nature of OPRA, spanning multiple exchanges, and featuring numerous options contracts characterized by diverse attributes. With an optimized Spark runtime, Athena helps the analysis of petabytes of data by dynamically scaling the number of Spark engines is less than a second.

Marketing 82

Marketing Analytics Visualization Strategy 82

datapine

SEPTEMBER 29, 2022

Engineered to be the “Swiss Army Knife” of data development, these processes prepare your organization to face the challenges of digital age data, wherever and whenever they appear. Data quality management is a set of practices that aim at maintaining a high quality of information. But first, let’s define what data quality actually is.

Data Quality 241

Data Quality Metrics Data-driven Management 241

AWS Big Data

SEPTEMBER 29, 2023

XML files are well-suited for applications, but they may not be optimal for analytics engines. In order to enhance query performance and enable easy access in downstream analytics engines such as Amazon Athena , it’s crucial to preprocess XML files into a columnar format like Parquet. xml and technique2.xml.

Metadata 65

Metadata Visualization Data-driven Optimization 65

AWS Big Data

MARCH 3, 2023

Every event in the data source can be relevant, and our customers don’t tolerate data loss, poor data quality, or discrepancies between the source and Tricentis Analytics. Finally, data integrity is of paramount importance.

Software 52

Software Data Lake Testing Cost-Benefit 52

AWS Big Data

FEBRUARY 1, 2023

This post shows you how we migrated to a serverless data lake built on AWS that consumes data automatically from multiple sources and different formats. Furthermore, it created further opportunities for our data scientists and engineers to use AI and machine learning (ML) services to continuously feed and analyze data.

Optimization 52

Optimization Forecasting Data Lake Metadata 52

Domino Data Lab

AUGUST 10, 2021

Models can predict things before they happen more accurately than humans, such as catastrophic weather events or who is at risk of imminent death in a hospital. How to avoid falling for the “Model Myth” and build a model-driven business to sustain competitive advantage. What Is Modeling? Why Is Modeling Important?

Modeling 64

Modeling IT Risk Management Deep Learning 64

Domino Data Lab

JULY 2, 2019

Paco Nathan ‘s latest article covers program synthesis, AutoPandas, model-driven data queries, and more. SQL optimization provides helpful analogies, given how SQL queries get translated into query graphs internally , then the real smarts of a SQL engine work over that graph. Introduction. BTW, videos for Rev2 are up: [link].

Metadata 105

Metadata Machine Learning Data Science Data-driven 105

AWS Big Data

SEPTEMBER 13, 2023

The company wanted the ability to continue processing operational data in the secondary Region in the rare event of primary Region failure. AWS Glue is used to create source-aligned and consumer-aligned datasets and separate AWS Glue jobs to do feature engineering part of ML engineering and operations.

Data Lake 89

Data Lake Data Processing Metadata Snapshot 89

AWS Big Data

FEBRUARY 21, 2023

Data warehouses are mostly built using the dimensional model approach, which has consistently met business needs. The data vault approach solves most of the problems associated with dimensional models, but it brings other challenges in clinical quality control applications and regulatory reports. What is a data vault?

Data Warehouse 64

Data Warehouse Data Lake Cost-Benefit Modeling 64

AWS Big Data

AUGUST 1, 2023

In the world of software engineering and development, organizations use project management tools like Atlassian Jira Cloud. Companies often take a data lake approach to their analytics, bringing data from many different systems into one place to simplify how the analytics are done. Note that you may have multiple projects as well.

Data Lake 84

Data Lake Data Transformation Cost-Benefit Data-driven 84

Domino Data Lab

AUGUST 20, 2019

Many thanks to AWP Pearson for the permission to excerpt “Manual Feature Engineering: Manipulating Data for Fun and Profit” from the book, Machine Learning with Python for Everyone by Mark E. Feature engineering is useful for data scientists when assessing tradeoff decisions regarding the impact of their ML models.

Testing 68

Testing Modeling Interactive Measurement 68

IBM Big Data Hub

NOVEMBER 13, 2023

Kubernetes’s declarative, API -driven infrastructure has helped free up DevOps and other teams from manually driven processes so they can work more independently and efficiently to achieve their goals. This process allows applications to adjust to demand changes automatically, with speed, efficiency and minimal downtime.

Machine Learning 113

Machine Learning Data-driven Software Testing 113

CIO Business Intelligence

JUNE 29, 2022

Taking the broadest possible interpretation of data analytics , Azure offers more than a dozen services — and that’s before you include Power BI, with its AI-powered analysis and new datamart option , or governance-oriented approaches such as Microsoft Purview.

Data Lake 107

Data Lake Analytics Data Warehouse Machine Learning 107

IBM Big Data Hub

JULY 6, 2023

It is more challenging than ever for IT operations (ITOps) teams to maintain a complete view of their end-to-end IT environment and effectively manage events and incidents. A collaborative approach helps speed up the incident resolution process and greatly diminishes the need for traditional (and time-consuming) war rooms.

Management 55

Management IT Metrics Data-driven 55

DataRobot Blog

DECEMBER 20, 2022

In this context, an augmented intelligence approach around the data will be increasingly more critical for asset managers, investors, and real estate developers to ensure a better understanding of the real estate assets and take better decisions aimed at optimizing both the Net Asset Value and the Net Operating Income.

Management 59

Management Machine Learning Optimization Modeling 59

CIO Business Intelligence

AUGUST 15, 2023

That in turn has created a more engaging customer experience, which has helped boost the company’s search engine rankings, delivering more traffic to CarMax.com. That’s the message at the core of this year’s CIO 100 Awards for IT innovation and leadership , which recognize standout technology projects that meet such objectives.

IT 93

IT Manufacturing IoT Cost-Benefit 93

Alation

APRIL 14, 2022

In today’s AI/ML-driven world of data analytics, explainability needs a repository just as much as those doing the explaining need access to metadata, EG, information about the data being used. A useful feature for exposing patterns in the data. Automatic sampling to test transformation. Predictive Transformation. Scheduling.

Metadata 59

Metadata Data Governance Modeling Data-driven 59

Birst BI

JANUARY 29, 2019

Click here to register for January 31 Birst Smart Analytics live online launch event. A business user simply selects a KPI of interest, and machine learning algorithms run automatically across all data points that are related to generate the key reasons “why” a KPI is trending upward or downward.

Analytics 78

Analytics KPI Machine Learning Visualization 78

Alation

MARCH 1, 2022

There are many approaches to manage and use data. As data complexity increases and organizations become more ‘data driven’, catalogs will continue to rank as a high priority.”. With robust data lineage, data engineers can find and fix issues fast and prevent them from recurring. In the latest release of Alation, 2022.1

Data Warehouse 52

Data Warehouse Data Lake Risk Data-driven 52

Cloudera

SEPTEMBER 17, 2020

For enterprise organizations, managing and operationalizing increasingly complex data across the business has presented a significant challenge for staying competitive in analytic and data science driven markets. Enterprise Data Engineering From the Ground Up. Figure 1: Key component within CDP Data Engineering.

Visualization 102

Visualization Metrics Statistics Optimization 102

Sisense

MAY 11, 2021

Let’s say you want to subject a dataset to some form of anomaly detection; your model might take the form of a singular event stream that can be read by an anomaly detection service. let’s look at the raw product feature logs for customers in X industry paying us Y dollars). Discover why. What is data modeling?

Modeling 84

Modeling Big Data IoT Data Warehouse 84

DataRobot Blog

JUNE 24, 2022

That traditional approach normally included analyzing how real estate property assets performed in the past but also often looking for market trends. Traditional analytical approaches and data sources hamper the decision-making process to draw clear assumptions on market trends and develop robust and comprehensive business cases.

Forecasting 52

Forecasting Machine Learning Marketing Data-driven 52

CIO Business Intelligence

MARCH 28, 2024

By unifying these features, a far more comprehensive view of the patient is created, and thus, the potential for a more comprehensive treatment plan. Given the additional features and interpretability, LLMs can then help physicians make more informed decisions about disease trajectories, diagnoses, and risk factors of various diseases.

Unstructured Data 92

Unstructured Data Data-driven Risk Insurance 92

datapine

NOVEMBER 27, 2019

That way, any unexpected event will be immediately registered and the system will notify the user. Another feature that AI has on offer in BI solutions is the upscaled insights capability. Another feature that AI has on offer in BI solutions is the upscaled insights capability. Agile and flexible.

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361