AWS Big Data

NOVEMBER 29, 2023

dbt is an open source, SQL-first templating engine that allows you to write repeatable and extensible data transforms in Python and SQL. dbt is predominantly used by data warehouses (such as Amazon Redshift ) customers who are looking to keep their data transform logic separate from storage and engine.

Data Lake 103

Data Lake Management Metrics Data Warehouse 103

AWS Big Data

APRIL 26, 2023

The manufacturers need to know BMW Group’s exact current and future semiconductor volume information, which will effectively help steer the available worldwide supply. To enable this use case, we used the BMW Group’s cloud-native data platform called the Cloud Data Hub.

Forecasting 122

Forecasting Manufacturing Data Lake Big Data 122

CIO Business Intelligence

FEBRUARY 16, 2023

“Digitizing was our first stake at the table in our data journey,” he says. That step, primarily undertaken by developers and data architects, established data governance and data integration. That step, primarily undertaken by developers and data architects, established data governance and data integration.

Unstructured Data 102

Unstructured Data Data Lake Prescriptive Analytics Digital Transformation 102

DataKitchen

JULY 27, 2023

Here are a few examples that we have seen of how this can be done: Batch ETL with Azure Data Factory and Azure Databricks: In this pattern, Azure Data Factory is used to orchestrate and schedule batch ETL processes. Azure Blob Storage serves as the data lake to store raw data. Azure Machine Learning). So go ahead.

Machine Learning 130

Machine Learning Cost-Benefit Data Transformation Testing 130

AWS Big Data

NOVEMBER 13, 2023

Amazon Redshift is a fully managed data warehousing service that offers both provisioned and serverless options, making it more efficient to run and scale analytics without having to manage your data warehouse. Additionally, data is extracted from vendor APIs that includes data related to product, marketing, and customer experience.

Data Warehouse 92

Data Warehouse Data Lake Analytics Data Science 92

Ontotext

FEBRUARY 12, 2024

Organizational culture is a key factor in determining the viability and success of a data mesh initiative. Empowering individual domains and integrating them as a cohesive whole requires a reevaluation of various aspects of the business, including how data and information are managed and shared.

Data-driven 59

Data-driven Data Lake Data Quality Business Objectives 59

AWS Big Data

DECEMBER 21, 2023

To bring their customers the best deals and user experience, smava follows the modern data architecture principles with a data lake as a scalable, durable data store and purpose-built data stores for analytical processing and data consumption.

Data Lake 89

Data Lake Data Warehouse Data-driven B2B 89

Cloudera

NOVEMBER 29, 2021

Data transforms businesses. That’s where the data lifecycle comes into play. Managing data and its flow, from the edge to the cloud, is one of the most important tasks in the process of gaining data intelligence. . The firm also worked on creating a solid pipeline from the data warehouse to the data lake.

Data Lake 77

Data Lake Data Warehouse Data Architecture Reporting 77

Cloudera

OCTOBER 11, 2021

Modak Nabu reliably curates datasets for any line of business and personas, from business analysts to data scientists. Customers using Modak Nabu with CDP today have deployed Data Lakes and. An executive dashboard shows the status of crawlers, pipelines, and data profiling. Modak Nabu TM and CDE’s Spark-on-Kubernetes.

Data Lake 95

Data Lake Cost-Benefit Data-driven Dashboards 95

Smarten

AUGUST 4, 2023

If your team has easy-to-use tools and features, you are much more likely to experience the user adoption you want and to improve data literacy and data democratization across the organization. Machine learning capability determines the best techniques, and the best fit transformations for data so that the outcome is clear and concise.

Data Lake 52

Data Lake Machine Learning Data Integration Optimization 52

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 104

Data Warehouse Testing Data Quality Reporting 104

AWS Big Data

APRIL 11, 2023

By collecting data from store sensors using AWS IoT Core , ingesting it using AWS Lambda to Amazon Aurora Serverless , and transforming it using AWS Glue from a database to an Amazon Simple Storage Service (Amazon S3) data lake, retailers can gain deep insights into their inventory and customer behavior.

Forecasting 76

Forecasting Management IoT Data-driven 76

AWS Big Data

DECEMBER 21, 2023

As the volume and complexity of analytics workloads continue to grow, customers are looking for more efficient and cost-effective ways to ingest and analyse data. For more information, see Setting up networking for development for AWS Glue. This enables organizations to streamline data integration and analytics with OpenSearch Service.

Analytics 96

Analytics IT Data Lake Visualization 96

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. Prior to his current role, he was VP of Analytics at AWS, where he worked across the entire AWS database portfolio.

Dashboards 73

Dashboards Data-driven Data Integration Data Lake 73

AWS Big Data

FEBRUARY 6, 2023

Finally, we show you the technical information to use the tool. Use case overview Migrating Hadoop workloads to Amazon EMR accelerates big data analytics modernization, increases productivity, and reduces operational cost. Refactoring coupled compute and storage to a decoupling architecture is a modern data solution.

Cost-Benefit 52

Cost-Benefit Data Lake Dashboards Big Data 52

AWS Big Data

MARCH 3, 2023

Building data lakes from continuously changing transactional data of databases and keeping data lakes up to date is a complex task and can be an operational challenge. You can then apply transformations and store data in Delta format for managing inserts, updates, and deletes. Choose Create stack.

Data Lake 83

Data Lake Dashboards Metrics Metadata 83

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.

Data Warehouse 52

Data Warehouse Reporting Data Transformation Sales 52

AWS Big Data

APRIL 25, 2024

In the era of data, organizations are increasingly using data lakes to store and analyze vast amounts of structured and unstructured data. Data lakes provide a centralized repository for data from various sources, enabling organizations to unlock valuable insights and drive data-driven decision-making.

Optimization 65

Optimization Data Lake Cost-Benefit Reporting 65

Cloudera

OCTOBER 13, 2020

CDP Data Hub: a VM/Instance-based service that allows IT and developers to build custom business applications for a diverse set of use cases with secure, self-service access to enterprise data. . Predict – Data Engineering (Apache Spark). This is Now. New Services.

Data Warehouse 97

Data Warehouse Machine Learning Visualization Data Lake 97

AWS Big Data

FEBRUARY 6, 2023

Then it retrieves the job history information (YARN logs from application managers) by calling the YARN ResourceManager application API. For more information on how to use the YARN log organizer, refer to the yarn-log-organizer GitHub repo. This information helps you understand who submits an application to a queue.

Dashboards 76

Dashboards Optimization Data Lake Cost-Benefit 76

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. While aggregating, summarizing, and aligning to a common information model, all transformations must not affect the integrity of data from its source.

Software 52

Software Data Lake Testing Cost-Benefit 52

Cloudera

JUNE 1, 2021

After all, we invented the whole idea of Big Data. Well, at Cloudera, we envision a world where everyone can quickly and easily access the data-powered information and insights they need – in just a few clicks. . The mission is to “Make data and analytics easy and accessible, for everyone.” 650-644-3900.

Uncertainty 144

Uncertainty Cost-Benefit Risk Strategy 144

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 69

Reporting Metrics Optimization Data Lake 69

DataKitchen

DECEMBER 9, 2022

By streamlining data-related workflows and enabling real-time collaboration, DataOps can help organizations to quickly turn data into insights, and to put those insights into action. This can include analyzing data to identify patterns and trends, and using predictive analytics to forecast future outcomes and guide decision making.

Machine Learning 130

Machine Learning Data-driven Optimization Modeling 130

IBM Big Data Hub

OCTOBER 16, 2023

Most of today’s largest foundation models, including the large language model (LLM) powering ChatGPT, have been trained on information culled from the internet. But how trustworthy is that training data? It helps you streamline data engineering with reduced data pipelines, simplified data transformation and enriched data.

Risk 70

Risk Modeling Management Metadata 70

CIO Business Intelligence

OCTOBER 18, 2022

Resultant recommended a new, on-prem data infrastructure, complete with data lakes to provide stake holders with a better way to manage data reliability, accuracy, and timeliness. I think you have to toot your own horn that, yes, we have this information available.”. They want that information,” she says.

Data Transformation 141

Data Transformation Consulting Data Lake Reporting 141

Alation

MARCH 22, 2022

The table details are extracted from the IDF pipeline information, which then syncs details like column, table, business, and technical metadata. This produces end-to-end lineage so business and technology users alike can understand the state of a data lake and/or lake house. Transparency is key.

Metadata 52

Metadata Cost-Benefit Data Quality Data Lake 52

AWS Big Data

OCTOBER 27, 2023

Efficiency : Data transformation tasks that previously took weeks or months can now be accomplished within minutes, optimizing efficiency. In this tutorial, we walk through the entire process, from setting up the connection to running the data transfer flow. For more information on AWS Glue, visit AWS Glue.

Analytics 95

Analytics Visualization Data Integration Cost-Benefit 95

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. Creating a High-Quality Data Pipeline.

Data Governance 40

Data Governance Risk Metadata Management 40

AWS Big Data

APRIL 5, 2023

The platform also provides analytics and insights to support successful information sharing and fuel continuous improvement. In 2021, Showpad decided to take the next step in its data evolution and set forth the vision to power innovation, product decisions, and customer engagement using data-driven insights.

Dashboards 52

Dashboards Reporting Cost-Benefit Visualization 52

AWS Big Data

FEBRUARY 8, 2023

This approach doesn’t solve for data quality issues in source systems, and doesn’t remove the need to have a wholistic data quality strategy. For addressing data quality challenges in Amazon Simple Storage Service (Amazon S3) data lakes and data pipelines, AWS has announced AWS Glue Data Quality (preview).

Data Quality 76

Data Quality Testing Data Warehouse Unstructured Data 76

AWS Big Data

JUNE 29, 2023

In our solution, we create a notebook to access automotive sensor data, enrich the data, and send the enriched output from the Kinesis Data Analytics Studio notebook to an Amazon Kinesis Data Firehose delivery stream for delivery to an Amazon Simple Storage Service (Amazon S3) data lake.

Data Analytics 74

Data Analytics Analytics IoT Data Lake 74

Sisense

MAY 11, 2021

The reasons for this are simple: Before you can start analyzing data, huge datasets like data lakes must be modeled or transformed to be usable. According to a recent survey conducted by IDC , 43% of respondents were drawing intelligence from 10 to 30 data sources in 2020, with a jump to 64% in 2021!

Modeling 84

Modeling Big Data IoT Data Warehouse 84

IBM Big Data Hub

JANUARY 18, 2023

In another decade, the internet and mobile started the generate data of unforeseen volume, variety and velocity. It required a different data platform solution. Hence, Data Lake emerged, which handles unstructured and structured data with huge volume. Data lakehouse was created to solve these problems.

Data Lake 52

Data Lake Data Warehouse Data-driven Metadata 52

O'Reilly on Data

OCTOBER 19, 2021

ML use cases rarely dictate the master data management solution, so the ML stack needs to integrate with existing data warehouses. You want to carefully manage consistency of data between training and predictions, as well as make sure that there’s no leakage of information when models are being trained and tested with historical data.

IT 351

IT Testing Experimentation Software 351

IBM Big Data Hub

JULY 17, 2023

These encoder-only architecture models are fast and effective for many enterprise NLP tasks, such as classifying customer feedback and extracting information from large documents. 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.

Machine Learning 62

Machine Learning Data Warehouse Modeling Cost-Benefit 62

Alation

AUGUST 11, 2022

Today, the brightest minds in our industry are targeting the massive proliferation of data volumes and the accompanying but hard-to-find value locked within all that data. But there are only so many data engineers available in the market today; there’s a big skills shortage.

Metadata 52

Metadata Data Warehouse Data Quality Data Lake 52