Cloudera

FEBRUARY 8, 2021

Continuing from my previous blog post about how awesome and easy it is to develop web-based applications backed by Cloudera Operational Database (COD), I started a small project to integrate COD with another CDP cloud experience, Cloudera Machine Learning (CML). . b) Basic data transformation. Go to runner.py and run it.

Machine Learning 71

Machine Learning Statistics Modeling Dashboards 71

Cloudera

AUGUST 8, 2022

The general availability covers Iceberg running within some of the key data services in CDP, including Cloudera Data Warehouse ( CDW ), Cloudera Data Engineering ( CDE ), and Cloudera Machine Learning ( CML ). Cloudera Data Engineering (Spark 3) with Airflow enabled. Cloudera Machine Learning .

Snapshot 87

Snapshot Data Warehouse Machine Learning Cost-Benefit 87

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 84

Data Lake Metrics Testing Cost-Benefit 84

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. Prerequisites You need the following resources: Python 3.9 jobs locally using a Docker container. aws:/home/glue_user/.aws

Data Integration 69

Data Integration Snapshot Testing Visualization 69

AWS Big Data

JULY 31, 2023

We create the insert_orders_fact_tbl AWS Glue job manually using AWS Glue Visual Studio. Select Visual with a blank canvas , then choose Create. Navigate to the Visual tab. Under Add nodes , enter Glue in the search bar and choose AWS Glue Data Catalog (Source) to add the Data Catalog as the source.

Sales 52

Sales Data Warehouse Visualization Testing 52

Alation

FEBRUARY 2, 2023

Many are subject matter experts for a particular kind of data, which enables them to spot anomalies in that data quickly, understand the root cause, and resolve the issue. Image Sourced from theproductmanager.com Further, they can quickly create helpful visualizations from the data they analyze.

Management 52

Management Data-driven Visualization Strategy 52

AWS Big Data

APRIL 25, 2023

The following AWS services are used for data ingestion, processing, and load: Amazon AppFlow is a fully managed integration service that enables you to securely transfer data between SaaS applications like Salesforce, SAP, Marketo, Slack, and ServiceNow, and AWS services like Amazon S3 and Amazon Redshift , in just a few clicks.

Sales 69

Sales Visualization Software Marketing 69

AWS Big Data

FEBRUARY 6, 2023

In this post, we dive deep into the tool, walking through all steps from log ingestion, transformation, visualization, and architecture design to calculate TCO. With QuickSight, you can visualize YARN log data and conduct analysis against the datasets generated by pre-built dashboard templates and a widget.

Dashboards 72

Dashboards Optimization Data Lake Cost-Benefit 72

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. These experts can define transformations from streams to tables and govern the processing progress using a visual, SQL-based interface.

Dashboards 98

Dashboards IoT Optimization Internet of Things 98

DataKitchen

JULY 27, 2023

You can use it for big data analytics and machine learning workloads. Azure Databricks Delta Live Table s: These provide a more straightforward way to build and manage Data Pipelines for the latest, high-quality data in Delta Lake. Azure Blob Storage serves as the data lake to store raw data.

Machine Learning 130

Machine Learning Cost-Benefit Data Transformation Testing 130

Sisense

MARCH 14, 2021

Before we dive into the topics of big data as a service and analytics applied to same, let’s quickly clarify data analytics using an oft-used application of analytics: Visualization! As we move from right to left in the diagram, from big data to BI, we notice that unstructured data transforms into structured data. (ESB

Big Data 52

Big Data IoT Data Warehouse Data-driven 52

O'Reilly on Data

JANUARY 17, 2023

Think about what the model results tell you: “Maybe a random forest isn’t the best tool to split this data, but XLNet is.” ” If none of your models performed well, that tells you that your dataset–your choice of raw data, feature selection, and feature engineering–is not amenable to machine learning.

Machine Learning 325

Machine Learning Predictive Modeling Software Modeling 325

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. Everything is visual. Azure Synapse Analytics.

Data Lake 111

Data Lake Analytics Data Warehouse Machine Learning 111

AWS Big Data

OCTOBER 11, 2023

The availability of machine-readable files opens up new possibilities for data analytics, allowing organizations to analyze large amounts of pricing data. Using machine learning (ML) and data visualization tools, these datasets can be transformed into actionable insights that can inform decision-making.

Visualization 92

Visualization Dashboards Data-driven Gap analysis 92

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.

Dashboards 91

Dashboards Analytics Metadata Optimization 91

AWS Big Data

OCTOBER 27, 2023

Overview of AWS Glue AWS Glue is a serverless data integration service that makes it easier to discover, prepare, and combine data for analytics, machine learning (ML), and application development. AWS Glue provides both visual and code-based interfaces to make data integration easier. Open AWS Glue console.

Analytics 92

Analytics Visualization Data Integration Cost-Benefit 92

AWS Big Data

JULY 6, 2023

It has not been specifically designed for heavy data transformation tasks. Step Functions helps developers use AWS services to build distributed applications, automate processes, orchestrate microservices, and create data and machine learning (ML) pipelines. Add a data source block.

Machine Learning 126

Machine Learning Visualization IoT Digital Transformation 126

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).

Data Lake 84

Data Lake Cost-Benefit Data Integration Data Transformation 84

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. Automated development: Automates data preparation, model development, feature engineering and hyperparameter optimization using AutoAI.

Machine Learning 65

Machine Learning Data Warehouse Modeling Cost-Benefit 65

Cloudera

AUGUST 17, 2021

When we announced the GA of Cloudera Data Engineering back in September of last year, a key vision we had was to simplify the automation of data transformation pipelines at scale. Typically users need to ingest data, transform it into optimal format with quality checks, and optimize querying of the data by visual analytics tool.

Management 110

Management Cost-Benefit Data Transformation Optimization 110

Alation

JUNE 28, 2022

Scale effectively: Leverage taxonomies to ensure consistent modeling outcomes when introducing new data sets or changing business demands. Track data lineage: Document data origins, record data transformation and movement, and visualize flow throughout the entire data lifecycle.

Metadata 52

Metadata Management Data Governance Machine Learning 52

Cloudera

OCTOBER 14, 2020

Apache Spark unifies batch processing, real-time processing, stream analytics, machine learning, and interactive query in one-platform. Also, such a concept helps admin to visualize the jobs which are scheduled for debugging purposes. Background. Why choose K8s for Apache Spark. Acknowledgments.

Machine Learning 112

Machine Learning Management Big Data Optimization 112

Octopai

JANUARY 19, 2021

With Octopai’s support and analysis of Azure Data Factory, enterprises can now view complete end-to-end data lineage from Azure Data Factory all the way through to reporting for the first time ever. The post NEW: Octopai Announces Support of Microsoft Azure Data Factory appeared first on Octopai.

Metadata 52

Metadata ROI Optimization Data Quality 52

Sisense

MAY 11, 2021

Data teams dealing with larger, faster-moving cloud datasets needed more robust tools to perform deeper analyses and set the stage for next-level applications like machine learning and natural language processing. But this was only the tip of the analytics iceberg. One solution with immense potential is ”edge computing.”

Modeling 84

Modeling Big Data IoT Data Warehouse 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. Missing values can be filled in based on expert knowledge, heuristics, or by some machine learning techniques.

Testing 68

Testing Modeling Interactive Measurement 68

AWS Big Data

OCTOBER 5, 2023

With Amazon AppFlow, you can run data flows at nearly any scale at the frequency you choose—on a schedule, in response to a business event, or on demand. You can configure data transformation capabilities such as filtering and validation to generate rich, ready-to-use data as part of the flow itself, without additional steps.

Data Warehouse 82

Data Warehouse Machine Learning Data Integration Data-driven 82

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. This integration empowers users to go from data to predictions and visualizations faster than ever.

Dashboards 73

Dashboards Data-driven Data Integration Data Lake 73

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!

Data-driven 49

Data-driven Machine Learning Business Intelligence Consulting 49

Rocket-Powered Data Science

MARCH 20, 2023

Data collections are the ones and zeroes that encode the actionable insights (patterns, trends, relationships) that we seek to extract from our data through machine learning and data science. incorporates the business context of the data and data products that are being recommended and delivered).

Data Warehouse 324

Data Warehouse Metadata Digital Transformation Unstructured Data 324

FineReport

MARCH 31, 2024

In 2024, business intelligence (BI) software has undergone significant advancements, revolutionizing data management and decision-making processes. Harnessing the power of advanced APIs, automation, and AI, these tools simplify data compilation, organization, and visualization, empowering users to extract actionable insights effortlessly.

Dashboards 52

Dashboards Visualization Data mining Data-driven 52

CIO Business Intelligence

APRIL 30, 2024

Together the technologies aim to help business users and “novice” data analysts explore their data and gain insights without having to resort to data experts. This is really empowering everyone to be a data expert,” Maxon said. “It Shared Dimensions and Composable Data Sources.

Analytics 73

Analytics Metrics Visualization Dashboards 73

AWS Big Data

AUGUST 1, 2023

Although Jira Cloud provides reporting capability, loading this data into a data lake will facilitate enrichment with other business data, as well as support the use of business intelligence (BI) tools and artificial intelligence (AI) and machine learning (ML) applications. Choose Update.

Data Lake 82

Data Lake Data Transformation Cost-Benefit Data-driven 82

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.

IoT 100

IoT Machine Learning Optimization Internet of Things 100

Cloudera

NOVEMBER 22, 2021

In addition, data pipelines include more and more stages, thus making it difficult for data engineers to compile, manage, and troubleshoot those analytical workloads. As a result, alternative data integration technologies (e.g.,

Data Processing 88

Data Processing Data Warehouse Enterprise Visualization 88

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.

Dashboards 52

Dashboards Reporting Cost-Benefit Visualization 52

Jet Global

MAY 1, 2023

This is in contrast to traditional BI, which extracts insight from data outside of the app. We rely on increasingly mobile technology to comb through massive amounts of data and solve high-value problems. Plus, there is an expectation that tools be visually appealing to boot. Their dashboards were visually stunning.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52

Jet Global

FEBRUARY 23, 2024

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. Data mapping is important for several reasons.

Data Warehouse 52

Data Warehouse Reporting Data Transformation Sales 52