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 Data Science 52

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 88

Data Warehouse Machine Learning Data Integration Data-driven 88

Cloudera

OCTOBER 13, 2020

In the beginning, CDP ran only on AWS with a set of services that supported a handful of use cases and workload types: CDP Data Warehouse: a kubernetes-based service that allows business analysts to deploy data warehouses with secure, self-service access to enterprise data. That Was Then. New Services.

Data Warehouse 94

Data Warehouse Machine Learning Visualization Data Lake 94

DataKitchen

OCTOBER 5, 2021

A DataOps Engineer owns the assembly line that’s used to build a data and analytic product. We find it helpful to think of data operations as a factory. That’s the state of data analytics today. . Figure 2: Data operations can be conceptualized as a series of automated factory assembly lines.

Testing 152

Testing Dashboards Measurement Experimentation 152

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 ). Cloudera Data Engineering (Spark 3) with Airflow enabled. Cloudera Machine Learning .

Snapshot 91

Snapshot Data Warehouse Machine Learning Cost-Benefit 91

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 86

Data Lake Data Architecture Metadata Data Warehouse 86

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. Manageability and use for non-technical users, democratizing data enterprisewide.

Dashboards 72

Dashboards Reporting Data Warehouse Structured Data 72

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

IBM Big Data Hub

JULY 5, 2023

Data Lakes have been around for well over a decade now, supporting the analytic operations of some of the largest world corporations. 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.

Data Lake 62

Data Lake Metadata Cost-Benefit Data Warehouse 62

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 64

Machine Learning Data Warehouse Modeling Cost-Benefit 64

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. Prescriptive analytics.

Visualization 135

Visualization Cost-Benefit Big Data Prescriptive Analytics 135

datapine

SEPTEMBER 29, 2022

6) Data Quality Metrics Examples. 7) Data Quality Control: Use Case. 8) The Consequences Of Bad Data Quality. 9) 3 Sources Of Low-Quality Data. 10) Data Quality Solutions: Key Attributes. Industry-wide, the positive ROI on quality data is well understood. 4 – Data Reporting. With a shocking 2.5

Data Quality 241

Data Quality Metrics Data-driven Management 241

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

AUGUST 1, 2023

Although Jira Cloud provides reporting capability, loading this data into a data lake will facilitate enrichment with other business data, as well as support the use of business intelligence (BI) tools and artificial intelligence (AI) and machine learning (ML) applications. For InitialRunFlag , choose Setup. Choose Update.

Data Lake 88

Data Lake Data Transformation Cost-Benefit Data-driven 88

CDW Research Hub

OCTOBER 25, 2019

As we review data transformation and modernization strategies with our clients, we find many are investigating Snowflake as a data warehouse solution due to its ease of use, speed, and increased flexibility over a traditional data warehouse offering.

Data Warehouse 40

Data Warehouse Testing Strategy Data-driven 40

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 73

Risk Modeling Management Metadata 73

IBM Big Data Hub

MARCH 14, 2024

The solution: IBM databases on AWS To solve for these challenges, IBM’s portfolio of SaaS database solutions on Amazon Web Services (AWS), enables enterprises to scale applications, analytics and AI across the hybrid cloud landscape. It enables secure data sharing for analytics and AI across your ecosystem.

Cost-Benefit 78

Cost-Benefit Metadata Optimization Management 78

Sisense

MARCH 30, 2021

In Gartner’s Top 10 Data and Analytics Trends for 2021, trend No. The Sisense Fusion platform embodies this idea, empowering every user to embrace analytics via actionable intelligence delivered directly to them where they spend their time. The Sisense Q1 2021 release is focused on bringing customized analytics to each person.

Dashboards 52

Dashboards Machine Learning Data Warehouse Marketing 52

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. CRM platforms).

Data Processing 92

Data Processing Data Warehouse Enterprise Visualization 92

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

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. Why are they so popular?

Metadata 52

Metadata Data Warehouse Data Quality Data Lake 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

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. Bindu Chandramohan, Lead, Data Analytics, Alation : Thanks, Jason!

Metrics 52

Metrics Dashboards Sales Reporting 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. Choose Confirm.

Sales 52

Sales Data Warehouse Visualization Testing 52

Sisense

MAY 11, 2021

You can’t talk about data analytics without talking about data modeling. These two functions are nearly inseparable as we move further into a world of analytics that blends sources of varying volume, variety, veracity, and velocity. But this was only the tip of the analytics iceberg.

Modeling 84

Modeling Big Data IoT Data Warehouse 84

Ontotext

FEBRUARY 12, 2024

Transferring ownership of data/datasets to domain-specific units that possess a deeper understanding of rules around the data empowers teams, improves data quality and trust, and greatly accelerates the building of data models and analytics.

Data-driven 59

Data-driven Data Lake Data Quality Business Objectives 59

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 79

Data Quality Testing Data Warehouse Unstructured Data 79

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 72

Reporting Metrics Optimization Data Lake 72

Occam's Razor

OCTOBER 19, 2010

What is the first thing you want when you think about web analytics? 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 (!!), recommending tools for the complete web analytics 2.0 Web Analytics 2.0.

Analytics 135

Analytics Testing Measurement Optimization 135

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 53

Enterprise IT Digital Transformation Data Warehouse 53

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

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 96

Data Lake Snapshot Big Data Data-driven 96

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

You can then apply transformations and store data in Delta format for managing inserts, updates, and deletes. Amazon EMR Serverless is a serverless option in Amazon EMR that makes it easy for data analysts and engineers to run open-source big data analytics frameworks without configuring, managing, and scaling clusters or servers.

Data Lake 86

Data Lake Dashboards Metrics Metadata 86