DataKitchen

JANUARY 3, 2022

There’s a recent trend toward people creating data lake or data warehouse patterns and calling it data enablement or a data hub. DataOps expands upon this approach by focusing on the processes and workflows that create data enablement and business analytics. DataOps Process Hub.

Business Analytics 245

Business Analytics Analytics Testing Dashboards 245

DataKitchen

OCTOBER 11, 2021

The data engineer then emails the BI Team, who refreshes a Tableau dashboard. Figure 1: Example data pipeline with manual processes. There are no automated tests , so errors frequently pass through the pipeline. Finally, when your implementation is complete, you can track and measure your process.

Testing 152

Testing Metadata Dashboards Statistics 152

AWS Big Data

MAY 30, 2024

Amazon Redshift is a fast, scalable, and fully managed cloud data warehouse that allows you to process and run your complex SQL analytics workloads on structured and semi-structured data. It also helps you securely access your data in operational databases, data lakes, or third-party datasets with minimal movement or copying of data.

Data Warehouse 85

Data Warehouse Data Lake Cost-Benefit Structured Data 85

O'Reilly on Data

OCTOBER 19, 2021

We need robust versioning for data, models, code, and preferably even the internal state of applications—think Git on steroids to answer inevitable questions: What changed? The applications must be integrated to the surrounding business systems so ideas can be tested and validated in the real world in a controlled manner.

IT 342

IT Testing Experimentation Software 342

Corinium

JUNE 6, 2019

Some of the work is very foundational, such as building an enterprise data lake and migrating it to the cloud, which enables other more direct value-added activities such as self-service. It is also important to have a strong test and learn culture to encourage rapid experimentation. Incorporate these into subsequent releases.

Insurance 250

Insurance Analytics Forecasting Deep Learning 250

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 94

Data Warehouse Data Lake Analytics Data Science 94

AWS Big Data

NOVEMBER 8, 2023

Amazon Redshift Serverless is a fully managed cloud data warehouse that allows you to seamlessly create your data warehouse with no infrastructure management required. Redshift Serverless measures data warehouse capacity in Redshift Processing Units (RPUs), which are part of the compute resources.

Data Lake 78

Data Lake Data Warehouse Cost-Benefit Optimization 78

AWS Big Data

MARCH 27, 2024

Amazon Redshift is a fast, scalable, and fully managed cloud data warehouse that allows you to process and run your complex SQL analytics workloads on structured and semi-structured data. It also helps you securely access your data in operational databases, data lakes, or third-party datasets with minimal movement or copying of data.

Testing 101

Testing Data Warehouse Metrics Cost-Benefit 101

Cloudera

APRIL 4, 2022

Numerous factors helped accelerate the vaccine roll-out including prior research, genome sequencing, jumping the FDA approval queue and a plethora of testing volunteers. The Impact of Data and Analytics. The usage of data lakes and automation are helping facilitate the data sharing and collaboration across the healthcare ecosystem.

Data Lake 79

Data Lake Digital Transformation Manufacturing Sales 79

AWS Big Data

MARCH 3, 2023

Tricentis is the global leader in continuous testing for DevOps, cloud, and enterprise applications. Speed changes everything, and continuous testing across the entire CI/CD lifecycle is the key. Tricentis instills that confidence by providing software tools that enable Agile Continuous Testing (ACT) at scale.

Software 52

Software Data Lake Testing Cost-Benefit 52

Smart Data Collective

FEBRUARY 20, 2022

Data storage databases. Your SaaS company can store and protect any amount of data using Amazon Simple Storage Service (S3), which is ideal for data lakes, cloud-native applications, and mobile apps. Well, let’s find out. Artificial intelligence (AI). You can therefore trust its reliability.

Cost-Benefit 115

Cost-Benefit Data Lake Software Machine Learning 115

IBM Big Data Hub

APRIL 9, 2024

This allows the Masters to scale analytics and AI wherever their data resides, through open formats and integration with existing databases and tools. “Hole distances and pin positions vary from round to round and year to year; these factors are important as we stage the data.”

Management 80

Management IT Machine Learning Metrics 80

datapine

APRIL 15, 2020

Your Chance: Want to test an agile business intelligence solution? Business intelligence is moving away from the traditional engineering model: analysis, design, construction, testing, and implementation. Test BI in a small group and deploy the software internally. Finalize testing. Without further ado, let’s begin.

Business Intelligence 276

Business Intelligence Analytics Testing Dashboards 276

AWS Big Data

AUGUST 22, 2023

The features of AWS Glue, which include a scheduler for automating tasks, code generation for ETL (extract, transform, and load) processes, notebook integration for interactive development and debugging, as well as robust security and compliance measures, make it a convenient and cost-effective solution for archival and restoration needs.

Data Processing 90

Data Processing Testing Data Lake Data Integration 90

AWS Big Data

MAY 18, 2023

You can discover and connect to over 70 diverse data sources, manage your data in a centralized data catalog, and create, run, and monitor data integration pipelines to load data into your data lakes and your data warehouses. Refer to Develop and test AWS Glue version 3.0 runtime ( 3.5

Testing 79

Testing Data Lake Cost-Benefit Data Integration 79

BI-Survey

AUGUST 21, 2020

Advanced analytics and new ways of working with data also create new requirements that surpass the traditional concepts. Many companies are therefore forced to put these concepts to the test. But what are the right measures to make the data warehouse and BI fit for the future?

Data Warehouse 98

Data Warehouse Data Lake Data Governance Data Architecture 98

CIO Business Intelligence

SEPTEMBER 12, 2022

Collectively, the agencies also have pilots up and running to test electric buses and IoT sensors scattered throughout the transportation system. We’re just making sure the company is aware that this capability does exist, and that we are ready to build whatever business challenge or business problem that’s been identified using data.

Data Warehouse 113

Data Warehouse Predictive Analytics Data Lake IoT 113

AWS Big Data

OCTOBER 23, 2023

Modern applications store massive amounts of data on Amazon Simple Storage Service (Amazon S3) data lakes, providing cost-effective and highly durable storage, and allowing you to run analytics and machine learning (ML) from your data lake to generate insights on your data.

Data Lake 104

Data Lake Visualization Optimization Interactive 104

Jet Global

JANUARY 15, 2021

You might measure those costs in different ways, including actual dollars and cents, staff time, added complexity, and risk. Most of those things are not about direct monetary costs; they are less tangible and measurable, but nonetheless very important. In other words, switching costs are not just about money.

Cost-Benefit 72

Cost-Benefit Data Lake Reporting OLAP 72

BI-Survey

JANUARY 15, 2023

In general, central data & analytics teams determine the data architecture for analytical data, decoupled from the landscape of operational data sources. Indeed, this is what the data warehouse, data lake and data lakehouse have in common, regardless of the differences in their detail.

Data Warehouse 52

Data Warehouse IT Data Architecture Measurement 52

AWS Big Data

JUNE 6, 2023

AWS Glue Data Quality allows you to measure and monitor the quality of data in your data repositories. It’s important for business users to be able to see quality scores and metrics to make confident business decisions and debug data quality issues. Avik Bhattacharjee is a Senior Partner Solutions Architect at AWS.

Data Quality 74

Data Quality Metrics Visualization Dashboards 74

Jet Global

JANUARY 18, 2021

Perhaps more importantly, it provides an opportunity for the organization to implement measures in advance that can reduce risk, lower costs, and improve the end result. In a separate blog post, we discussed the potential for using a data warehouse as a means for automating data extraction and transformation in advance of system migration.

Data Lake 98

Data Lake Reporting Cost-Benefit Finance 98

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 86

Enterprise Data Warehouse Snapshot Cost-Benefit 86

Alation

FEBRUARY 17, 2023

The firms that get data governance and management “right” bring people together and leverage a set of capabilities: (1) Agile; (2) Six sigma; (3) data science; and (4) project management tools. The overall program should set a 2-year vision, mission, and goals, and then focus on execution, measuring progress along the way.

Data Governance 52

Data Governance Data Quality Metadata Cost-Benefit 52

CIO Business Intelligence

SEPTEMBER 6, 2022

It’ being everything from how they collect and measure data, to how they understand it and their own glossary. Cataloging your data is more important than ever for many companies, with so many technology options, different data silos, enterprise warehousing, lake houses, data lakes, and all those types of capabilities,” says Pimblett.

IT 75

IT Forecasting Data Lake Enterprise 75

CIO Business Intelligence

OCTOBER 18, 2023

Gen AI boom in the making Many early and established forays into generative AI are being developed on the AI platforms of cloud leaders Microsoft, Google, and Amazon, reportedly with numerous guardrails and governance measures in place to contain unrestricted exploration. First, we launched a private instance of GPT-3.5

Risk 129

Risk Manufacturing Enterprise Technology 129

AWS Big Data

MAY 25, 2023

Many organizations today are using AWS Glue to build ETL pipelines that bring data from disparate sources and store the data in repositories like a data lake, database, or data warehouse for further consumption.

Reporting 72

Reporting Metrics Optimization Data Lake 72

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 79

Data Quality Testing Data Warehouse Unstructured Data 79

Cloudera

FEBRUARY 16, 2022

blueberry spacing) is a measure of the model’s interpretability. In the case of CDP Public Cloud, this includes virtual networking constructs and the data lake as provided by a combination of a Cloudera Shared Data Experience (SDX) and the underlying cloud storage. The complete list is shown below: Model Lineage .

Machine Learning 83

Machine Learning Modeling Metadata Recreation/Entertainment 83

AWS Big Data

JULY 19, 2023

We are now able to import data from Google Cloud Storage to Amazon S3. Scaling considerations In this example, we set the AWS Glue capacity as 10 DPU (Data Processing Units). A DPU is a relative measure of processing power that consists of 4 vCPUs of compute capacity and 16 GB of memory.

Big Data 85

Big Data Software Consulting Unstructured Data 85

Sisense

OCTOBER 6, 2020

Most commonly, we think of data as numbers that show information such as sales figures, marketing data, payroll totals, financial statistics, and other data that can be counted and measured objectively. This is quantitative data. It’s “hard,” structured data that answers questions such as “how many?”

Statistics 98

Statistics Unstructured Data Data-driven Visualization 98

Alation

MARCH 22, 2022

DataOps requires an array of technology to automate the design, development, deployment, and management of data delivery, with governance sprinkled on for good measure. This produces end-to-end lineage so business and technology users alike can understand the state of a data lake and/or lake house.

Metadata 52

Metadata Cost-Benefit Data Quality Data Lake 52

AWS Big Data

JULY 25, 2023

It automatically provisions and intelligently scales data warehouse compute capacity to deliver fast performance, and you pay only for what you use. Just load your data and start querying right away in the Amazon Redshift Query Editor or in your favorite business intelligence (BI) tool. Ashish has over 24 years of experience in IT.

Metrics 83

Metrics Data Warehouse Dashboards Snapshot 83

Cloudera

JUNE 6, 2019

While this approach provides isolation, it creates another significant challenge: duplication of data, metadata, and security policies, or ‘split-brain’ data lake. Now the admins need to synchronize multiple copies of the data and metadata and ensure that users across the many clusters are not viewing stale information.

Metadata 86

Metadata Data Lake Optimization Strategy 86

Alation

APRIL 14, 2022

A useful feature for exposing patterns in the data. Supports the ability to interact with the actual data and perform analysis on it. Automatic sampling to test transformation. Similar to a data warehouse schema, this prep tool automates the development of the recipe to match. Record-keeping in a data catalog is key.

Metadata 59

Metadata Data Governance Modeling Data-driven 59

AWS Big Data

APRIL 5, 2023

Showpad also struggled with data quality issues in terms of consistency, ownership, and insufficient data access across its targeted user base due to a complex BI access process, licensing challenges, and insufficient education. The entire data team of 20 people were “all on hands on deck” for the project.

Dashboards 52

Dashboards Reporting Cost-Benefit Visualization 52

CIO Business Intelligence

SEPTEMBER 21, 2023

One thing buyers have to be careful about is the security measures vendors put in place. What happens if you upload your data to these AIs?” To make all this possible, the data had to be collected, processed, and fed into the systems that needed it in a reliable, efficient, scalable, and secure way.

Enterprise 124

Enterprise Consulting Modeling Cost-Benefit 124