AWS Big Data

OCTOBER 14, 2024

Enterprise data is brought into data lakes and data warehouses to carry out analytical, reporting, and data science use cases using AWS analytical services like Amazon Athena , Amazon Redshift , Amazon EMR , and so on. Maintaining lists of possible values for the columns requires continuous updates.

Metadata 105

Metadata Data Lake Modeling Data Warehouse 105

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 95

Reporting Metrics Optimization Data Lake 95

CIO Business Intelligence

JUNE 29, 2022

Analytics is the means for discovering those insights, and doing it well requires the right tools for ingesting and preparing data, enriching and tagging it, building and sharing reports, and managing and protecting your data and insights. Azure Data Factory. Azure Data Lake Analytics.

Data Lake 116

Data Lake Analytics Data Warehouse Machine Learning 116

AWS Big Data

DECEMBER 13, 2023

In addition to using native managed AWS services that BMS didn’t need to worry about upgrading, BMS was looking to offer an ETL service to non-technical business users that could visually compose data transformation workflows and seamlessly run them on the AWS Glue Apache Spark-based serverless data integration engine.

Metadata 111

Metadata Data Lake Visualization Data Quality 111

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 122

Data Lake Management Metrics Data Warehouse 122

AWS Big Data

DECEMBER 21, 2023

The data products used inside the company include insights from user journeys, operational reports, and marketing campaign results, among others. The data platform serves on average 60 thousand queries per day. The data volume is in double-digit TBs with steady growth as business and data sources evolve.

Data Lake 115

Data Lake Data Warehouse Data-driven B2B 115

AWS Big Data

JANUARY 6, 2025

With Amazon AppFlow, you can run data flows at nearly any scale and at the frequency you chooseon 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.

Analytics 98

Analytics Data Warehouse Metrics Big Data 98

CIO Business Intelligence

AUGUST 3, 2023

Model, understand, and transform the data Comcast faced the challenge of collecting large amounts of information about potential security and reliability issues but with no easy way to make sense of it all, says Noopur Davis, corporate EVP, CISO, and chief product privacy officer.

Analytics 98

Analytics Data Lake Metadata Cost-Benefit 98

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 111

Data Warehouse Analytics Data Lake Data Science 111

Cloudera

JUNE 30, 2022

These tools empower analysts and data scientists to easily collaborate on the same data, with their choice of tools and analytic engines. No more lock-in, unnecessary data transformations, or data movement across tools and clouds just to extract insights out of the data.

Data Lake 88

Data Lake Data Warehouse Data Architecture Metadata 88

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

AWS Big Data

SEPTEMBER 5, 2024

Amazon Redshift , a warehousing service, offers a variety of options for ingesting data from diverse sources into its high-performance, scalable environment. Federated queries are useful for use cases where organizations want to combine data from their operational systems with data stored in Amazon Redshift.

IoT 111

IoT Data Warehouse Cost-Benefit Reporting 111

DataKitchen

JULY 27, 2023

Azure Blob Storage serves as the data lake to store raw data. Azure Databricks, a big data analytics platform built on Apache Spark, performs the actual data transformations. As part of these workflows, Azure Functions can be used to perform small pieces of data transformation logic.

Machine Learning 130

Machine Learning Cost-Benefit Data Transformation Testing 130

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 126

Data Warehouse Testing Data Quality Reporting 126

AWS Big Data

AUGUST 1, 2024

However, you might face significant challenges when planning for a large-scale data warehouse migration. Trace the flow of data from its origins in the source systems, through the data warehouse, and ultimately to its consumption by reporting, analytics, and other downstream processes.

Data Warehouse 115

Data Warehouse KPI Optimization Cost-Benefit 115

AWS Big Data

AUGUST 19, 2024

One crucial business requirement for the ecommerce company is to generate a Pricing Summary Report that provides a detailed analysis of pricing and discounting strategies. This report is essential for understanding revenue streams, identifying opportunities for optimization, and making data-driven decisions regarding pricing and promotions.

Analytics 119

Analytics Data-driven Data Integration Data Lake 119

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. This is the scale and speed that cloud-native solutions can provide — and Modak Nabu with CDP has been delivering the same.

Data Lake 95

Data Lake Cost-Benefit Data-driven Dashboards 95

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. . Enrich – Data Engineering (Apache Spark and Apache Hive). Predict – Data Engineering (Apache Spark). This is Now.

Data Warehouse 97

Data Warehouse Machine Learning Visualization Data Lake 97

AWS Big Data

AUGUST 13, 2024

With AWS Glue, you can discover and connect to hundreds of diverse data sources and manage your data in a centralized data catalog. It enables you to visually create, run, and monitor extract, transform, and load (ETL) pipelines to load data into your data lakes. Select Visual ETL in the central pane.

Data Processing 115

Data Processing Visualization Data Lake Data Processing 115

Cloudera

OCTOBER 7, 2022

dbt allows data teams to produce trusted data sets for reporting, ML modeling, and operational workflows using SQL, with a simple workflow that follows software engineering best practices like modularity, portability, and continuous integration/continuous development (CI/CD). The Open Data Lakehouse . Introduction.

Data Warehouse 81

Data Warehouse Data Transformation Machine Learning Data Lake 81

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

Enterprise 111

Enterprise Data Warehouse Data Lake Optimization 111

IBM Big Data Hub

JANUARY 18, 2023

Data platform architecture has an interesting history. Towards the turn of millennium, enterprises started to realize that the reporting and business intelligence workload required a new solution rather than the transactional applications. A read-optimized platform that can integrate data from multiple applications emerged.

Data Lake 52

Data Lake Data Warehouse Data-driven Metadata 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 72

Optimization Data Lake Cost-Benefit Reporting 72

IBM Big Data Hub

OCTOBER 16, 2023

How to scale AL and ML with built-in governance A fit-for-purpose data store built on an open lakehouse architecture allows you to scale AI and ML while providing built-in governance tools. A data store lets a business connect existing data with new data and discover new insights with real-time analytics and business intelligence.

Risk 70

Risk Modeling Management Metadata 70

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

AWS Big Data

FEBRUARY 6, 2023

The Amazon EMR TCO report with the new Amazon EMR design can demonstrate the Amazon EMR migration with detailed cost saving and business benefits. It enables compute such as EMR instances and storage such as Amazon Simple Storage Service (Amazon S3) data lakes to scale. The following figures show the TCO report.

Cost-Benefit 52

Cost-Benefit Data Lake Dashboards Big Data 52

AWS Big Data

MARCH 3, 2023

Although Tricentis has amassed such data over a decade, the data remains untapped for valuable insights. Each of these tools has its own reporting capabilities that make it difficult to combine the data for integrated and actionable business insights.

Software 52

Software Data Lake Testing Cost-Benefit 52

AWS Big Data

APRIL 5, 2023

The company decided to use AWS to unify its business intelligence (BI) and reporting strategy for both internal organization-wide use cases and in-product embedded analytics targeted at its customers. In this post, we share how Showpad used QuickSight to streamline data and insights access across teams and customers.

Dashboards 52

Dashboards Reporting Cost-Benefit Visualization 52

DataKitchen

DECEMBER 9, 2022

Observability in DataOps refers to the ability to monitor and understand the performance and behavior of data-related systems and processes, and to use that information to improve the quality and speed of data-driven decision making. The data scientists and IT professionals were amazed, and they couldn’t believe their eyes.

Machine Learning 130

Machine Learning Data-driven Optimization Data Analytics 130

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

IBM Big Data Hub

MARCH 14, 2024

Whether it’s for ad hoc analytics, data transformation, data sharing, data lake modernization or ML and gen AI, you have the flexibility to choose.  Netezza and Cognos now process over 5,200 reports daily, providing decision support for leadership across the business. With Netezza support for 1.2

Cost-Benefit 75

Cost-Benefit Metadata Optimization Management 75

Jet Global

MAY 9, 2024

A data pipeline is a series of processes that move raw data from one or more sources to one or more destinations, often transforming and processing the data along the way. This can include tasks such as data ingestion, cleansing, filtering, aggregation, or standardization.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 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.

Data Warehouse 52

Data Warehouse Reporting Data Transformation Visualization 52

Jet Global

OCTOBER 1, 2024

Trino allows users to run ad hoc queries across massive datasets, making real-time decision-making a reality without needing extensive data transformations. This is particularly valuable for teams that require instant answers from their data. Data Lake Analytics: Trino doesn’t just stop at databases.

Dashboards 52

Dashboards Data Lake Reporting Cost-Benefit 52

AWS Big Data

APRIL 28, 2025

Many organizations turn to data lakes for the flexibility and scale needed to manage large volumes of structured and unstructured data. Recently, NI embarked on a journey to transition their legacy data lake from Apache Hive to Apache Iceberg. NIs leading brands, Top10.com

Data Lake 67

Data Lake Metadata Cost-Benefit Snapshot 67

AWS Big Data

APRIL 29, 2025

While enabling organization-wide efficiency, the team also applied these principles to the data architecture, making sure that CLEA itself operates frugally. After evaluating various tools, we built a serverless data transformation pipeline using Amazon Athena and dbt. The Source stage maintains raw data in its original form.

Data Transformation 54

Data Transformation Cost-Benefit Testing Data Lake 54

AWS Big Data

NOVEMBER 14, 2024

We use the built-in features of Data Firehose, including AWS Lambda for necessary data transformation and Amazon Simple Notification Service (Amazon SNS) for near real-time alerts. APIs act as the entry point for applications to access data, business logic, or functionality from your backend services.

Data Lake 105

Data Lake Metadata Testing Data-driven 105