datapine

MAY 2, 2023

The rise of SaaS business intelligence tools is answering that need, providing a dynamic vessel for presenting and interacting with essential insights in a way that is digestible and accessible. The future is bright for logistics companies that are willing to take advantage of big data.

Big Data 275

Big Data Cost-Benefit Internet of Things Optimization 275

AWS Big Data

NOVEMBER 9, 2023

In this post, we delve into a case study for a retail use case, exploring how the Data Build Tool (dbt) was used effectively within an AWS environment to build a high-performing, efficient, and modern data platform. It does this by helping teams handle the T in ETL (extract, transform, and load) processes.

Data Warehouse 100

Data Warehouse Testing Data Quality Reporting 100

Cloudera

APRIL 19, 2022

Data holds incredible untapped potential for Australian organisations across industries, regardless of individual business goals, and all organisations are at different points in their data transformation journey with some achieving success faster than others. .

Data-driven 92

Data-driven Data Strategy Strategy Big Data 92

AWS Big Data

APRIL 26, 2023

We also split the data transformation into several modules (Data Aggregation, Data Filtering, and Data Preparation) to make the system more transparent and easier to maintain. Although each module is specific to a data source or a particular data transformation, we utilize reusable blocks inside of every job.

Manufacturing 118

Manufacturing Forecasting Data Lake Big Data 118

Cloudera

MARCH 14, 2023

Once a draft has been created or opened, developers use the visual Designer to build their data flow logic and validate it using interactive test sessions. In the DataFlow Designer, you can create Test Sessions to turn the canvas into an interactive interface that gives you all the feedback you need to quickly iterate your flow design.

Testing 84

Testing Publishing Metadata Interactive 84

Ontotext

MARCH 20, 2024

Make data-driven decisions with cutting-edge ML: Gain deeper insights from your data with the Accelerator’s cutting-edge ML capabilities. This allows your teams to make informed decisions based on real data, not just intuition. Zenia Graph’s Salesforce Accelerator makes this a reality.

Data-driven 52

Data-driven Strategy Sales Data Integration 52

FineReport

MARCH 7, 2024

As we explore examples of data analysis reports and interactive report data analysis dashboards, we embark on a journey to unravel the nuanced art of transforming raw data into meaningful narratives that empower decision-makers. Try FineReport Now 1. Try FineReport Now 1.1

Dashboards 52

Dashboards Reporting Advertising Statistics 52

Smart Data Collective

FEBRUARY 20, 2020

In 2015, Spend Matters wrote a detailed report on the applications of big data in the e-invoicing industry. Big Data Transforms Invoicing Software Applications. Before big data became a prominent aspect of invoicing, many SME owners don’t initially see much value in the concept of invoicing software. It’s Customizable.

Big Data 112

Big Data Software Reporting Interactive 112

bridgei2i

NOVEMBER 17, 2020

The Lean AI wave can be imagined as a 4 step process: AI use case discovery: Identify the current processes amenable to data and AI driven improvement, design the solution roadmap and proactively think through the potential failure modes of enterprise adoption.

Deep Learning 85

Deep Learning Manufacturing Optimization Data-driven 85

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 ). In the final stage of our ETL pipeline, we load new data into this partition. Using CDW with Iceberg.

Snapshot 92

Snapshot Data Warehouse Machine Learning Cost-Benefit 92

IBM Big Data Hub

OCTOBER 16, 2023

They are used in everything from robotics to tools that reason and interact with humans. A data store lets a business connect existing data with new data and discover new insights with real-time analytics and business intelligence. Foundation models can use language, vision and more to affect the real world.

Risk 76

Risk Modeling Management Metadata 76

AWS Big Data

MARCH 13, 2024

You can also use the data transformation feature of Data Firehose to invoke a Lambda function to perform data transformation in batches. Query the data using Athena Athena is a serverless, interactive analytics service built to analyze unstructured, semi-structured, and structured data where it is hosted.

Analytics 90

Analytics IoT Metadata Internet of Things 90

AWS Big Data

MAY 16, 2023

In this series of posts, we walk you through how we use Amazon QuickSight , a serverless, fully managed, business intelligence (BI) service that enables data-driven decision making at scale. The AWS Glue Data Catalog contains the table definitions for the smart sensor data sources stored in the S3 buckets.

Dashboards 74

Dashboards Statistics Data Collection Business Intelligence 74

FineReport

APRIL 21, 2024

Limited Interactivity Even after overcoming logistical and analytical hurdles to deploy embedded dashboards, the challenges persist. Empowering client-facing analysts to drive customization without extensive backend involvement is crucial for overcoming the limitations of traditional BI tools and enhancing interactivity.

Dashboards 52

Dashboards Visualization Interactive Business Intelligence 52

AWS Big Data

APRIL 30, 2024

Amazon Q Developer can now generate complex data integration jobs with multiple sources, destinations, and data transformations. Generated jobs can use a variety of data transformations, including filter, project, union, join, and custom user-supplied SQL. Configure an IAM role to interact with Amazon Q.

Data Integration 98

Data Integration Data Lake Data Warehouse Software 98

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. Feel free to explore your data now. You can also interact with filters on the right hand filter panel.

Dashboards 98

Dashboards IoT Optimization Internet of Things 98

AWS Big Data

JANUARY 17, 2024

Next, we create an AWS Cloud9 interactive development environment (IDE). Melody Yang is a Senior Big Data Solution Architect for Amazon EMR at AWS. She is an experienced analytics leader working with AWS customers to provide best practice guidance and technical advice in order to assist their success in data transformation.

Data Lake 89

Data Lake Snapshot Big Data Data-driven 89

AWS Big Data

MAY 9, 2023

For workloads such as data transforms, joins, and queries, you can use G.1X With exponentially growing data sources and data lakes, customers want to run more data integration workloads, including their most demanding transforms, aggregations, joins, and queries. 1X (1 DPU) and G.2X You can enable G.4X

Data Lake 84

Data Lake Cost-Benefit Data Integration Data Transformation 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.

Data Integration 69

Data Integration Snapshot Testing Visualization 69

Ontotext

APRIL 4, 2019

Milena Yankova : The professions of the future are related to understanding and processing data, transforming it into information and extracting knowledge from it. Milena Yankova : If they decide to work in IT, I would advise them to better understand the value of the data that machines collect from their interactions with us.

Recreation/Entertainment 76

Recreation/Entertainment Testing Enterprise Knowledge Discovery 76

AWS Big Data

NOVEMBER 15, 2023

The difference lies in when and where data transformation takes place. In ETL, data is transformed before it’s loaded into the data warehouse. In ELT, raw data is loaded into the data warehouse first, then it’s transformed directly within the warehouse.

Dashboards 91

Dashboards Analytics Metadata Data Warehouse 91

AWS Big Data

OCTOBER 11, 2023

We introduce you to Amazon Managed Service for Apache Flink Studio and get started querying streaming data interactively using Amazon Kinesis Data Streams. Traditionally, such a legacy call center analytics platform would be built on a relational database that stores data from streaming sources.

Management 101

Management Metadata Analytics Dashboards 101

AWS Big Data

OCTOBER 11, 2023

Due to this low complexity, the solution uses AWS serverless services to ingest the data, transform it, and make it available for analytics. Use the Data Catalog and transform the hospital price transparency data. When the data is available in the Data Catalog, you can develop the analytics query using Athena.

Visualization 92

Visualization Dashboards Data-driven Gap analysis 92

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 Transformation Business Intelligence 52

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.

Big Data 77

Big Data Data Processing Interactive Testing 77

CIO Business Intelligence

JUNE 29, 2022

But the features in Power BI Premium are now more powerful than the functionality in Azure Analysis Services, so while the service isn’t going away, Microsoft will offer an automated migration tool in the second half of this year for customers who want to move their data models into Power BI instead. Azure Data Factory.

Data Lake 116

Data Lake Analytics Data Warehouse Machine Learning 116

AWS Big Data

JULY 27, 2023

DataBrew is a visual data preparation tool that enables you to clean and normalize data without writing any code. The over 200 transformations it provides are now available to be used in an AWS Glue Studio visual job. Create a DataBrew recipe Start by registering the data store for the claims file.

Visualization 78

Visualization Cost-Benefit Data Quality Interactive 78

Alation

OCTOBER 27, 2022

Few actors in the modern data stack have inspired the enthusiasm and fervent support as dbt. This data transformation tool enables data analysts and engineers to transform, test and document data in the cloud data warehouse. Jason: What’s the value of using dbt with the data catalog ?

Metrics 52

Metrics Dashboards Sales Reporting 52

IBM Big Data Hub

JANUARY 18, 2023

This adds an additional ETL step, making the data even more stale. Data lakehouse was created to solve these problems. The data warehouse storage layer is removed from lakehouse architectures. Instead, continuous data transformation is performed within the BLOB storage. Each node can be different from the others.

Data Lake 52

Data Lake Data Warehouse Data-driven Metadata 52

Cloudera

JUNE 17, 2022

With Inbound Connections and NiFi’s ListenHTTP processor, users can now expose any NiFi flow through a stable endpoint that can be used by applications to send data to Kafka. To try out Inbound Connections on your own, take our interactive product tour or sign up for a free trial. .

Cost-Benefit 92

Cost-Benefit IoT Data Warehouse Manufacturing 92

AWS Big Data

FEBRUARY 6, 2023

For data pipeline orchestration, the Apache Airflow UI is a user-friendly tool that provides detailed views into your data pipeline. When it comes to pipeline health management, each service that your tasks are interacting with could be storing or publishing logs to different locations, such as an S3 bucket or Amazon CloudWatch logs.

Management 81

Management Interactive Metadata Publishing 81

Sisense

AUGUST 6, 2020

As an AI product manager, here are some important data-related questions you should ask yourself: What is the problem you’re trying to solve? What data transformations are needed from your data scientists to prepare the data? What are the right KPIs and outputs for your product? What will it take to build your MVP?

Management 95

Management Machine Learning Key Performance Indicator Cost-Benefit 95

AWS Big Data

JUNE 29, 2023

Solution overview For our use case, we use several AWS services to stream, ingest, transform, and analyze sample automotive sensor data in real time using Kinesis Data Analytics Studio. Kinesis Data Analytics Studio allows us to create a notebook, which is a web-based development environment. View the stream data.

Data Analytics 71

Data Analytics Analytics IoT Data Lake 71

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.

Enterprise 94

Enterprise Insurance Digital Transformation Interactive 94

AWS Big Data

NOVEMBER 16, 2023

Data Vault 2.0 allows for the following: Agile data warehouse development Parallel data ingestion A scalable approach to handle multiple data sources even on the same entity A high level of automation Historization Full lineage support However, Data Vault 2.0

Enterprise 81

Enterprise Data Warehouse Data Lake Optimization 81

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.

Machine Learning 116

Machine Learning Management Big Data Optimization 116

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.

Machine Learning 52

Machine Learning Sales Measurement ROI 52