Jet Global

MAY 9, 2024

The key components of a data pipeline are typically: Data Sources : The origin of the data, such as a relational database , data warehouse, data lake , file, API, or other data store. 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

AWS Big Data

FEBRUARY 16, 2023

Amazon Redshift is the most widely used data warehouse in the cloud, best suited for analyzing exabytes of data and running complex analytical queries. Amazon QuickSight is a fast business analytics service to build visualizations, perform ad hoc analysis, and quickly get business insights from your data.

Data Warehouse 77

Data Warehouse Sales Visualization Data Processing 77

AWS Big Data

MARCH 29, 2024

QuickSight makes it straightforward for business users to visualize data in interactive dashboards and reports. venvScriptsactivate.bat After this step, the subsequent steps run within the bounds of the virtual environment on the client machine and interact with the AWS account as needed. Choose Publish dashboard.

Metrics 104

Metrics Visualization Dashboards Interactive 104

AWS Big Data

MARCH 7, 2023

A data hub contains data at multiple levels of granularity and is often not integrated. It differs from a data lake by offering data that is pre-validated and standardized, allowing for simpler consumption by users. Data hubs and data lakes can coexist in an organization, complementing each other.

Analytics 69

Analytics Data Warehouse Data Lake Metadata 69

AWS Big Data

JANUARY 31, 2023

We have collected some of the key talks and solutions on data governance, data mesh, and modern data architecture published and presented in AWS re:Invent 2022, and a few data lake solutions built by customers and AWS Partners for easy reference.

Data Lake 79

Data Lake Data Governance Data Architecture Data Warehouse 79

AWS Big Data

APRIL 4, 2024

In the depicted architecture and our typical data lake use case, our data either resides n Amazon S3 or is migrated from on premises to Amazon S3 using replication tools such as AWS DataSync or AWS Database Migration Service (AWS DMS). It generates and publishes reports in Amazon S3, which are then accessible via Athena.

Data Quality 63

Data Quality Data Lake Data Warehouse Data-driven 63

AWS Big Data

SEPTEMBER 21, 2023

Satori integrates natively with both Amazon Redshift provisioned clusters and Amazon Redshift Serverless for easy setup of your Amazon Redshift data warehouse in the secure Satori portal. In part 2, we will explore how to set up self-service data access with Satori to data stored in Amazon Redshift.

Data Warehouse 84

Data Warehouse Interactive Data Architecture Data Lake 84

Ontotext

FEBRUARY 12, 2024

It proposes a technological, architectural, and organizational approach to solving data management problems by breaking up the monolithic data platform and de-centralizing data management across different domain teams and services. Once these domains interact and share data with each other, the mesh emerges.

IT 64

IT Metadata Data Quality Data Lake 64

IBM Big Data Hub

JULY 5, 2022

Back in the 1960s and 70s, vast amounts of data were stored in the world’s new mainframe computers—many of them IBM System/360 machines—and had become a problem. Finally, 13 years after Codd published his paper, IBM Db2 on z/OS was born, and 10 years after that the first IBM Db2 database for LUW was released. . They were expensive.

Data Lake 96

Data Lake Data Warehouse Publishing Structured Data 96

Ontotext

NOVEMBER 16, 2023

In a data mesh, domains are represented by a node, which can be an operational data store (ODS), a data warehouse, or a data lake tailored to the domain’s requirements. Mesh emerges when teams use other domains’ data products and the domains communicate with others in a governed manner.

Metadata 52

Metadata Data-driven Data Quality Data Architecture 52

Sisense

JUNE 30, 2020

Data visualization can either be static or interactive. Interactive visualizations enable users to drill down into data and extract and examine various views of the same dataset, selecting specific data points that they want to see in a visualized format. The role of visualizations in analytics.

Visualization 93

Visualization Analytics Dashboards Data-driven 93

Jet Global

FEBRUARY 23, 2024

This includes cleaning, aggregating, enriching, and restructuring data to fit the desired format. Load : Once data transformation is complete, the transformed data is loaded into the target system, such as a data warehouse, database, or another application.

Data Warehouse 52

Data Warehouse Reporting Data Transformation Sales 52

AWS Big Data

JULY 19, 2023

Amazon Redshift is a fully managed and petabyte-scale cloud data warehouse that is used by tens of thousands of customers to process exabytes of data every day to power their analytics workload. You can structure your data, measure business processes, and get valuable insights quickly can be done by using a dimensional model.

Modeling 67

Modeling Sales Data Warehouse Snapshot 67

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. Provide the following SQL statement.

Data Analytics 73

Data Analytics Analytics IoT Data Lake 73

Cloudera

APRIL 3, 2023

In this blog, we will share with you in detail how Cloudera integrates core compute engines including Apache Hive and Apache Impala in Cloudera Data Warehouse with Iceberg. We will publish follow up blogs for other data services. It allows us to independently upgrade the Virtual Warehouses and Database Catalogs.

Data Warehouse 79

Data Warehouse Snapshot Metadata Cost-Benefit 79

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

Cloudera

DECEMBER 12, 2018

After having rebuilt their data warehouse, I decided to take a little bit more of a pointed role, and I joined Oracle as a database performance engineer. I spent eight years in the real-world performance group where I specialized in high visibility and high impact data warehousing competes and benchmarks.

Data Warehouse 41

Data Warehouse Marketing Big Data Data Lake 41

Andrew White

JANUARY 11, 2021

This was for the Chief Data Officer, or head of data and analytics. Gartner also published the same piece of research for other roles, such as Application and Software Engineering. Data and Analytics Governance: Whats Broken, and What We Need To Do To Fix It. Link Data to Business Outcomes. Very interesting.

Data Analytics 52

Data Analytics Analytics Data-driven Finance 52

CIO Business Intelligence

SEPTEMBER 21, 2022

“The good news for many CIOs is that they’ve already laid the groundwork through investments in data governance and migration to the cloud,” LiveRamp noted in a recent report. Inconsistent data , which can result in inaccuracies in interacting with customers, and affect the internal operational use of data.

Risk 88

Risk Data Lake Marketing Interactive 88

IBM Big Data Hub

MAY 9, 2023

As AI becomes more pervasive, businesses need to feel confident that their models can be relied upon not to “hallucinate” facts or use inappropriate language when interacting with customers. With watsonx.data , businesses can quickly connect to data, get trusted insights and reduce data warehouse costs.

Data Warehouse 109

Data Warehouse Cost-Benefit Machine Learning Modeling 109

Domino Data Lab

APRIL 3, 2019

Most of the data management moved to back-end servers, e.g., databases. So we had three tiers providing a separation of concerns: presentation, logic, data. Note that data warehouse (DW) and business intelligence (BI) practices both emerged circa 1990. in lieu of simply landing in a data lake.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

IBM Big Data Hub

JULY 17, 2023

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. offers a Prompt Lab, where users can interact with different prompts using prompt engineering on generative AI models for both zero-shot prompting and few-shot prompting.

Machine Learning 67

Machine Learning Data Warehouse Modeling Cost-Benefit 67