DataRobot Blog

APRIL 4, 2022

Before the data is put into the model comes a process called feature engineering – transforming the original data columns to impose certain business assumptions or simply increase model accuracy. the model is able to explore a very wide set of “shapes” for adstock and find the one suggested by the data. Request a demo.

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Machine Learning Sales Measurement ROI 52

Sisense

OCTOBER 15, 2020

As real-time analytics and machine learning stream processing are growing rapidly, they introduce a new set of technological and conceptual challenges. Sisense is automatically joining the tables for us, and Upsolver keeps the data in both tables synced with the stream. Feel free to explore your data now.

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Dashboards IoT Optimization Internet of Things 98

AWS Big Data

JULY 26, 2023

Every time the business requirement changes (such as adding data sources or changing data transformation logic), you make changes on the AWS Glue app stack and re-provision the stack to reflect your changes. Then you will see a view similar to the following screenshot.

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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. Azure Data Factory. Azure Synapse Analytics. Datamarts in Power BI.

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Data Lake Analytics Data Warehouse Machine Learning 116

AWS Big Data

NOVEMBER 15, 2023

They can use their own toolsets or rely on provided blueprints to ingest the data from source systems. Once released, consumers use datasets from different providers for analysis, machine learning (ML) workloads, and visualization. The difference lies in when and where data transformation takes place.

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Dashboards Analytics Metadata Data Warehouse 98

AWS Big Data

MAY 9, 2023

Hundreds of thousands of customers use AWS Glue , a serverless data integration service, to discover, prepare, and combine data for analytics, machine learning (ML), and application development. AWS Glue for Apache Spark jobs work with your code and configuration of the number of data processing units (DPU).

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Data Lake Cost-Benefit Data Integration Data Transformation 91

AWS Big Data

OCTOBER 11, 2023

The data in the machine-readable files can provide valuable insights to understand the true cost of healthcare services and compare prices and quality across hospitals. The availability of machine-readable files opens up new possibilities for data analytics, allowing organizations to analyze large amounts of pricing data.

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Visualization Dashboards Data-driven Gap analysis 99

Sisense

AUGUST 6, 2020

AI and machine learning (ML) are not just catchy buzzwords; they’re vital to the future of our planet and your business. Doing it right can mean the difference between thriving in the new world of data and disappearing from it. What data transformations are needed from your data scientists to prepare the data?

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Management Machine Learning Key Performance Indicator Cost-Benefit 95

AWS Big Data

OCTOBER 18, 2023

They use various AWS analytics services, such as Amazon EMR, to enable their analysts and data scientists to apply advanced analytics techniques to interactively develop and test new surveillance patterns and improve investor protection. Melody Yang is a Senior Big Data Solutions Architect for Amazon EMR at AWS.

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Big Data Data Processing Interactive Testing 83

IBM Big Data Hub

JANUARY 18, 2023

They defined it as : “ A data lakehouse is a new, open data management architecture that combines the flexibility, cost-efficiency, and scale of data lakes with the data management and ACID transactions of data warehouses, enabling business intelligence (BI) and machine learning (ML) on all data. ”.

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Data Lake Data Warehouse Data-driven Metadata 52

IBM Big Data Hub

JULY 17, 2023

is our enterprise-ready next-generation studio for AI builders, bringing together traditional machine learning (ML) and new generative AI capabilities powered by foundation models. While they require task-specific labeled data for fine tuning, they also offer clients the best cost performance trade-off for non-generative use cases.

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Machine Learning Data Warehouse Modeling Cost-Benefit 65

AWS Big Data

FEBRUARY 6, 2023

The most common use case for Airflow is ETL (extract, transform, and load). Operationalizing machine learning (ML) is another growing use case, where data has to be transformed and normalized before it can be loaded into an ML model. format(S3_BUCKET_NAME), 's3://{}/data/aggregated/green'.format(S3_BUCKET_NAME),

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Management Interactive Metadata Publishing 87

Cloudera

OCTOBER 14, 2020

Apache Spark unifies batch processing, real-time processing, stream analytics, machine learning, and interactive query in one-platform. Background. Why choose K8s for Apache Spark. Acknowledgments. Thanks to Shaun Ahmadian and Dale Richardson for reviewing and sharing comments.

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Machine Learning Management Big Data Optimization 113

AWS Big Data

FEBRUARY 21, 2023

Solutions Architect – AWS SafeGraph is a geospatial data company that curates over 41 million global points of interest (POIs) with detailed attributes, such as brand affiliation, advanced category tagging, and open hours, as well as how people interact with those places. Dave Thibault is a Sr.

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Cost-Benefit Informatics Optimization Management 56

bridgei2i

SEPTEMBER 3, 2020

Ronobijay: Sure, I think it would, you know, what used to be anathema till a few months back, you know, data transformation is real now, right? It’s a real-time interaction. So what kind of application areas do you see for intelligent operations in the next few months? Now that is changing.

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Enterprise Insurance Digital Transformation Interactive 94

AWS Big Data

NOVEMBER 16, 2023

Amazon Redshift is a popular cloud data warehouse, offering a fully managed cloud-based service that seamlessly integrates with an organization’s Amazon Simple Storage Service (Amazon S3) data lake, real-time streams, machine learning (ML) workflows, transactional workflows, and much more—all while providing up to 7.9x

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Enterprise Data Warehouse Data Lake Optimization 87

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. Missing values can be filled in based on expert knowledge, heuristics, or by some machine learning techniques.

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Testing Modeling Interactive Measurement 68

AWS Big Data

NOVEMBER 7, 2023

Second, organizations still need transformations like cleansing, deduplication, and combining datasets for analysis and machine learning (ML). For these, AWS Glue provides fast, scalable data transformation.

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Dashboards Data-driven Data Integration Data Lake 74

Cloudera

OCTOBER 11, 2021

Modak Nabu relies on a framework of “Botworks”, a series of micro-jobs to accomplish various data transformation steps from ingestion to profiling, and indexing. Cloudera Data Engineering within CDP provides : Fully managed Spark-on-Kubernetes service that hides the complexity running production DE workloads at scale.

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Data Lake Cost-Benefit Data-driven Dashboards 89

Sisense

MAY 14, 2019

What was once a bold prediction is becoming more obvious by the day; current leaders in every industry are either disruptors that dominate legacy industries leveraging big data, or they’re traditional enterprises that see data as an opportunity to transform their products and services. Analytic builders of the world: Unite!

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Data-driven Machine Learning Business Intelligence Consulting 49

FineReport

MARCH 31, 2024

Furthermore, these tools boast customization options, allowing users to tailor data sources to address areas critical to their business success, thereby generating actionable insights and customizable reports. Best BI Tools for Data Analysts 3.1 Despite these drawbacks, Tableau remains a versatile and user-friendly BI tool.

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Dashboards Visualization Data mining Data-driven 52

CIO Business Intelligence

JANUARY 24, 2024

The Agent Swarm evolution has been propelled by advancements in computing, artificial intelligence (AI), machine learning (ML), and the Internet of Things (IoT). Use predefined rules, machine learning models, or a combination of both to make informed decisions.

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IoT Machine Learning Optimization Internet of Things 118

CIO Business Intelligence

APRIL 30, 2024

“But to us, it’s more than just having a data strategy; it’s also about building a great foundation of a data culture.” That’s where Tableau sees Pulse and Einstein Copilot for Tableau — a generative AI assistant that gives users the ability to interact with Tableau using natural language — coming in.

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IBM Big Data Hub

JUNE 15, 2023

A lakehouse should make it easy to combine new data from a variety of different sources, with mission critical data about customers and transactions that reside in existing repositories. New insights are found in the combination of new data with existing data, and the identification of new relationships.

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AWS Big Data

APRIL 5, 2023

Showpad built new customer-facing embedded dashboards within Showpad eOSTM and migrated its legacy dashboards to Amazon QuickSight , a unified BI service providing modern interactive dashboards, natural language querying, paginated reports, machine learning (ML) insights, and embedded analytics at scale.

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Dashboards Reporting Cost-Benefit Visualization 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. What is an ETL pipeline?

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Data Lake Data Warehouse Business Intelligence Machine Learning 52

Jet Global

MAY 1, 2023

This is in contrast to traditional BI, which extracts insight from data outside of the app. As rich, data-driven user experiences are increasingly intertwined with our daily lives, end users are demanding new standards for how they interact with their business data. Yes—but basic dashboards won’t be enough.

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Analytics Cost-Benefit Visualization Dashboards 52

Jet Global

FEBRUARY 23, 2024

This field guide to data mapping will explore how data mapping connects volumes of data for enhanced decision-making. Why Data Mapping is Important Data mapping is a critical element of any data management initiative, such as data integration, data migration, data transformation, data warehousing, or automation.

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