Sisense

MARCH 30, 2021

In Gartner’s Top 10 Data and Analytics Trends for 2021, trend No. Advanced data transformation with Custom Code. With enhanced live model connection parameters, you can now leverage one live data model for multiple customers who use the same schema structure in your data warehouse.

Dashboards 52

Dashboards Machine Learning Data Warehouse Marketing 52

Cloudera

APRIL 12, 2021

As Cussatt put it, “data transformation isn’t about the IT, but about enabling the mission to be able to serve the veterans.” Enterprise cloud offerings such as Cloudera Data Warehouse (CDW), a solution to evolving beyond shadow IT, deliver a hybrid cloud, multifunction data platform that centrally integrates information. .

Enterprise 52

Enterprise IT Digital Transformation Data Warehouse 52

AWS Big Data

JULY 31, 2023

This solution decouples the ETL and analytics workloads from our transactional data source Amazon Aurora, and uses Amazon Redshift as the data warehouse solution to build a data mart. We use Amazon Redshift as the data warehouse to implement the data mart solution. Under Transforms , choose SQL Query.

Sales 52

Sales Data Warehouse Visualization Testing 52

Sisense

MARCH 14, 2021

Attempting to learn more about the role of big data (here taken to datasets of high volume, velocity, and variety) within business intelligence today, can sometimes create more confusion than it alleviates, as vital terms are used interchangeably instead of distinctly.

Big Data 52

Big Data IoT Data Warehouse Data-driven 52

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. And there’s control of that landscape to facilitate insight and collaboration and limit risk.

Data Governance 40

Data Governance Risk Metadata Management 40

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 66

Reporting Metrics Optimization Data Lake 66

AWS Big Data

JANUARY 17, 2024

Apache Hudi is an open source transactional data lake framework that greatly simplifies incremental data processing and the development of data pipelines. Besides demonstrating with Hudi here, we will follow up with other OTF tables with other blogs. For Stack name , enter a stack name (for example, rsv2-emr-hudi-blog ).

Data Lake 89

Data Lake Snapshot Big Data Data-driven 89

Alation

JANUARY 17, 2023

The modern data stack is a combination of various software tools used to collect, process, and store data on a well-integrated cloud-based data platform. It is known to have benefits in handling data due to its robustness, speed, and scalability. A typical modern data stack consists of the following: A data warehouse.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Transformation Business Intelligence 52

Cloudera

OCTOBER 7, 2022

We’re excited to announce the general availability of the open source adapters for dbt for all the engines in CDP — Apache Hive , Apache Impala , and Apache Spark, with added support for Apache Livy and Cloudera Data Engineering. The Open Data Lakehouse . Cloudera builds dbt adaptors for all engines in the open data lakehouse.

Data Warehouse 79

Data Warehouse Data Transformation Testing Data Lake 79

DataKitchen

JULY 27, 2023

Azure Synapse Analytics Pipelines: Azure Synapse Analytics (formerly SQL Data Warehouse) provides data exploration, data preparation, data management, and data warehousing capabilities. It provides data prep, management, and enterprise data warehousing tools. It does the job.

Machine Learning 130

Machine Learning Cost-Benefit Data Transformation Testing 130

IBM Big Data Hub

JANUARY 18, 2023

They defined it as : “ A data lakehouse is a new, open data management architecture that combines the flexibility, cost-efficiency, and scale of data lakes with the data management and ACID transactions of data warehouses, enabling business intelligence (BI) and machine learning (ML) on all data. ”.

Data Lake 52

Data Lake Data Warehouse Data-driven Metadata 52

Cloudera

JUNE 17, 2022

In the second blog of the Universal Data Distribution blog series , we explored how Cloudera DataFlow for the Public Cloud (CDF-PC) can help you implement use cases like data lakehouse and data warehouse ingest, cybersecurity, and log optimization, as well as IoT and streaming data collection.

Cost-Benefit 88

Cost-Benefit IoT Data Warehouse Manufacturing 88

Alation

AUGUST 11, 2022

The data warehouse and analytical data stores moved to the cloud and disaggregated into the data mesh. 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. Subscribe to Alation's Blog.

Metadata 52

Metadata Data Warehouse Data Quality Data Lake 52

AWS Big Data

OCTOBER 27, 2023

AWS Glue , a serverless data integration and extract, transform, and load (ETL) service, has revolutionized this process, making it more accessible and efficient. AWS Glue eliminates complexities and costs, allowing organizations to perform data integration tasks in minutes, boosting efficiency.

Analytics 92

Analytics Visualization Data Integration Cost-Benefit 92

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 83

Data Lake Data Architecture Metadata Data Warehouse 83

IBM Big Data Hub

JULY 17, 2023

In this blog, I will cover: What is watsonx.ai? Capabilities within the Prompt Lab include: Summarize: Transform text with domain-specific content into personalized overviews and capture key points (e.g., It is supported by querying, governance, and open data formats to access and share data across the hybrid cloud.

Machine Learning 70

Machine Learning Data Warehouse Modeling Cost-Benefit 70

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. Curious to learn how the data catalog can power your data strategy?

Metrics 52

Metrics Dashboards Sales Reporting 52

Alation

OCTOBER 18, 2022

Data analysts and engineers use dbt to transform, test, and document data in the cloud data warehouse. Yet every dbt transformation contains vital metadata that is not captured – until now. Data Transformation in the Modern Data Stack. How did the data transform exactly?

Metadata 52

Metadata Metrics Recreation/Entertainment Data Quality 52

IBM Big Data Hub

MARCH 14, 2024

. With Db2 Warehouse’s fully managed cloud deployment on AWS, enjoy no overhead, indexing, or tuning and automated maintenance. 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.

Cost-Benefit 87

Cost-Benefit Metadata Optimization Management 87

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 76

Data Lake Data Warehouse Data Architecture Reporting 76

AWS Big Data

FEBRUARY 8, 2023

Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. Amazon Redshift enables you to run complex SQL analytics at scale and performance on terabytes to petabytes of structured and unstructured data, and make the insights widely available through popular business intelligence (BI) and analytics tools.

Data Quality 73

Data Quality Testing Data Warehouse Unstructured Data 73

Sisense

MAY 11, 2021

You can’t talk about data analytics without talking about data modeling. 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. This design philosophy was adapted from our friends at Fishtown Analytics.).

Modeling 84

Modeling Big Data IoT Data Warehouse 84

CDW Research Hub

JULY 23, 2021

Get hands-on experience with the data cloud. Gain experience and understanding of how to drive better business decisions with your data. Our fifth video will demonstrate data transformation and orchestration with Matillion into Snowflake. Learn about current trends.

Structured Data 52

Structured Data Consulting Strategy Data Strategy 52

AWS Big Data

MARCH 3, 2023

Data ingestion – Steps 1 and 2 use AWS DMS, which connects to the source database and moves full and incremental data (CDC) to Amazon S3 in Parquet format. Data transformation – Steps 3 and 4 represent an EMR Serverless Spark application (Amazon EMR 6.9 For Name , enter emr-delta-blog. For Type , choose Spark.

Data Lake 79

Data Lake Dashboards Metrics Metadata 79

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 99

Data Lake Management Metrics Data Warehouse 99

Occam's Razor

OCTOBER 19, 2010

I was reflecting on that recently and thought it was incredible that in all my years of writing this blog I have never written a blog post, not one single one (!!), My goal is to give you a list of tools that I use in my everyday life as a practitioner (you'll see many of them implemented on this blog). Disclosure].

Analytics 135

Analytics Testing Measurement Optimization 135

AWS Big Data

OCTOBER 5, 2023

Amazon AppFlow , a fully managed data integration service, has been at the forefront of streamlining data transfer between AWS services, software as a service (SaaS) applications, and now Google BigQuery. Architecture Let’s review the architecture to transfer data from Google BigQuery to Amazon S3 using Amazon AppFlow.

Data Warehouse 82

Data Warehouse Machine Learning Data Integration Data-driven 82

Smart Data Collective

OCTOBER 13, 2021

There are countless examples of big data transforming many different industries. There is no disputing the fact that the collection and analysis of massive amounts of unstructured data has been a huge breakthrough. This is something that you can learn more about in just about any technology blog.

Visualization 135

Visualization Cost-Benefit Big Data Prescriptive Analytics 135

IBM Big Data Hub

JUNE 15, 2023

It is comprised of commodity cloud object storage, open data and open table formats, and high-performance open-source query engines. To help organizations scale AI workloads, we recently announced IBM watsonx.data , a data store built on an open data lakehouse architecture and part of the watsonx AI and data platform.

Data Warehouse 102

Data Warehouse Data Lake Optimization Data-driven 102

AWS Big Data

AUGUST 1, 2023

Provision resources with AWS CloudFormation For the initial setup, you launch an AWS CloudFormation stack to create an S3 bucket to store data, IAM roles for data access, and the AWS Glue crawler and Data Catalog components. This will enable both the CDC steps and the data transformation steps for the Jira data.

Data Lake 81

Data Lake Data Transformation Cost-Benefit Data-driven 81

Ontotext

FEBRUARY 12, 2024

For many organizations, a centralized data platform will fall short as it gives data teams much less autonomy over managing increasingly diverse and voluminous datasets. A centralized data engineering team focuses on building a governed self-serviced infrastructure, while domain teams use the services to build full-stack data products.

Data-driven 59

Data-driven Data Lake Data Quality Business Objectives 59

AWS Big Data

SEPTEMBER 19, 2023

However, our legacy data warehouse-based solution was not equipped for this challenge. However, with a minimum data freshness of 10 minutes, this architecture inherently didn’t align with the near real-time fraud detection use case.

Analytics 75

Analytics Risk Big Data Machine Learning 75

CDW Research Hub

OCTOBER 20, 2020

In our latest demo, we highlight how we’re piloting a modern analytic solution using Snowflake’s scalable cloud data warehouse in combination with Matillion and ThoughtSpot, through Snowflake’s Partner Connect service offering. Creation of a dynamic report, allowing users to drill down on a 360-degree searchable dashboard.

Dashboards 72

Dashboards Reporting Data Warehouse Structured Data 72

IBM Big Data Hub

JULY 5, 2023

This was, without a question, a significant departure from traditional analytic environments, which often meant vendor-lock in and the inability to work with data at scale. Another unexpected challenge was the introduction of Spark as a processing framework for big data.

Data Lake 71

Data Lake Metadata Cost-Benefit Data Warehouse 71

Cloudera

NOVEMBER 22, 2021

In legacy analytical systems such as enterprise data warehouses, the scalability challenges of a system were primarily associated with computational scalability, i.e., the ability of a data platform to handle larger volumes of data in an agile and cost-efficient way. Introduction.

Data Processing 88

Data Processing Data Warehouse Enterprise Visualization 88

Jet Global

MARCH 13, 2024

Between complex data structures, data security questions, and error-prone manual processes, merging data from disparate sources into a single system can quickly turn your routine reporting processes into a stressful and time-consuming ordeal.

Reporting 52

Reporting Finance Data Quality Sales 52