AWS Big Data

AUGUST 3, 2023

With the rapid growth of technology, more and more data volume is coming in many different formats—structured, semi-structured, and unstructured. Data analytics on operational data at near-real time is becoming a common need. Then we can query the data with Amazon Athena visualize it in Amazon QuickSight.

Data Lake 78

Data Lake Visualization Dashboards Insurance 78

IBM Big Data Hub

SEPTEMBER 19, 2023

Though you may encounter the terms “data science” and “data analytics” being used interchangeably in conversations or online, they refer to two distinctly different concepts. Meanwhile, data analytics is the act of examining datasets to extract value and find answers to specific questions.

Data Science 84

Data Science Data Analytics Prescriptive Analytics Analytics 84

Dataiku

SEPTEMBER 1, 2023

Lately, the concept of data experience has been gaining attention in discussions around the enterprise data stack. As the name suggests, it refers to how people interact with data in enterprise settings. Due to fragmented data setups in these companies, their data lakes have the following characteristics:

Data Lake 69

Data Lake Data Analytics Analytics Interactive 69

Data Virtualization

AUGUST 19, 2021

“Data mesh” is a new data analytics paradigm proposed by Zhamak Dehghani, one that is designed to move organizations from monolithic architectures such as the data warehouse and the data lake to more decentralized architectures. As long-time supporters of logical.

Data Lake 98

Data Lake Data Warehouse Data Analytics Analytics 98

Data Virtualization

AUGUST 19, 2021

“Data mesh” is a new data analytics paradigm proposed by Zhamak Dehghani, one that is designed to move organizations from monolithic architectures such as the data warehouse and the data lake to more decentralized architectures. As long-time supporters of logical.

Data Lake 98

Data Lake Data Warehouse Data Analytics Analytics 98

DataKitchen

NOVEMBER 4, 2021

Cloud computing has made it much easier to integrate data sets, but that’s only the beginning. Creating a data lake has become much easier, but that’s only ten percent of the job of delivering analytics to users. It often takes months to progress from a data lake to the final delivery of insights.

Data Processing 246

Data Processing Data Lake Cost-Benefit Testing 246

DataKitchen

AUGUST 3, 2021

First-generation – expensive, proprietary enterprise data warehouse and business intelligence platforms maintained by a specialized team drowning in technical debt. Second-generation – gigantic, complex data lake maintained by a specialized team drowning in technical debt. The post What is a Data Mesh? See the pattern?

Data Architecture 246

Data Architecture Data Lake Cost-Benefit Data Warehouse 246

DataKitchen

DECEMBER 6, 2022

The two things we are most excited about are: First, DataOps is distinct from all Data Analytic tools. As founders, we sat in a room eight years ago (when all the rage was Hadoop, data prep, and data lakes) and debated — will there ever be an ‘ops’ layer that sits next to all the current data tools?

Software 130

Software Marketing Data Lake Testing 130

Cloudera

JUNE 18, 2022

Cloudera customers run some of the biggest data lakes on earth. These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. On data warehouses and data lakes.

Data Lake 89

Data Lake Data Warehouse Machine Learning Cost-Benefit 89

CDW Research Hub

JULY 18, 2022

One modern data platform solution that provides simplicity and flexibility to grow is Snowflake’s data cloud and platform. These Snowflake accelerators reduce the time to analytics for your users at all levels so you can make data-driven decisions faster. Security Data Lake. Snowflake Health Check.

Optimization 87

Optimization Data Lake Data Warehouse Manufacturing 87

DataKitchen

AUGUST 9, 2021

Instead of having a giant, unwieldy data lake , the data mesh breaks up the data and workflow assets into controllable and composable domains with inherent interdependencies. Domains are built from raw data and/or the output of other domains.

Testing 246

Testing Data Lake Metadata Publishing 246

DataKitchen

AUGUST 19, 2021

Figure 3 shows an example processing architecture with data flowing in from internal and external sources. Each data source is updated on its own schedule, for example, daily, weekly or monthly. The data scientists and analysts have what they need to build analytics for the user. The new Recipes run, and BOOM! Conclusion.

Data Warehouse 246

Data Warehouse Data Lake Manufacturing Testing 246

AWS Big Data

JANUARY 30, 2023

Many customers need an ACID transaction (atomic, consistent, isolated, durable) data lake that can log change data capture (CDC) from operational data sources. There is also demand for merging real-time data into batch data. Delta Lake framework provides these two capabilities. Choose Create role.

Insurance 77

Insurance Data Lake Data-driven Management 77

DataKitchen

AUGUST 27, 2021

Marketing invests heavily in multi-level campaigns, primarily driven by data analytics. This analytics function is so crucial to product success that the data team often reports directly into sales and marketing. The Otezla team built a system with tens of thousands of automated tests checking data and analytics quality.

Analytics 246

Analytics Sales Testing Cost-Benefit 246

DataKitchen

JANUARY 25, 2022

Previously, the consulting team had been using a patchwork of ETL to consolidate data from disparate sources into a data lake. In data analytics, automated orchestrations can handle data operations, testing, observability, data integration and all manner of data pipelines.

Consulting 244

Consulting Testing Data Lake Data Quality 244

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). Ramesh Raghupathy is a Senior Data Architect with WWCO ProServe at AWS.

Data Quality 61

Data Quality Data Lake Data Warehouse Data-driven 61

AWS Big Data

OCTOBER 9, 2023

Data lakes have been gaining popularity for storing vast amounts of data from diverse sources in a scalable and cost-effective way. As the number of data consumers grows, data lake administrators often need to implement fine-grained access controls for different user profiles.

Data Lake 119

Data Lake Testing Big Data Management 119

DataKitchen

JUNE 12, 2023

We had been talking about “Agile Analytic Operations,” “DevOps for Data Teams,” and “Lean Manufacturing For Data,” but the concept was hard to get across and communicate. I spent much time de-categorizing DataOps: we are not discussing ETL, Data Lake, or Data Science.

Testing 130

Testing Data Lake Dashboards Data Science 130

AWS Big Data

APRIL 3, 2023

Tens of thousands of customers run business-critical workloads on Amazon Redshift , AWS’s fast, petabyte-scale cloud data warehouse delivering the best price-performance. With Amazon Redshift, you can query data across your data warehouse, operational data stores, and data lake using standard SQL.

Data Warehouse 96

Data Warehouse Testing Data Lake Data-driven 96

AWS Big Data

JUNE 6, 2023

This is a guest blog post by Mira Daniels and Sean Whitfield from SumUp. Unless, of course, the rest of their data also resides in the Google Cloud. AWS Glue gave us a cost-efficient option to migrate the data and we further optimized storage cost by pruning cold data. It consists of full-day and intraday tables.

Analytics 55

Analytics Data Lake Testing Optimization 55

DataKitchen

JANUARY 3, 2022

A DataOps process hub offers a way for business analytics teams to cope with fast-paced requirements without expanding staff or sacrificing quality. Analytics Hub and Spoke. The data analytics function in large enterprises is generally distributed across departments and roles. DataOps Process Hub.

Business Analytics 245

Business Analytics Analytics Testing Dashboards 245

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. This blog post has demonstrated how AWS can greatly benefit your SaaS company, on multiple levels. Conclusions.

Cost-Benefit 115

Cost-Benefit Data Lake Software Machine Learning 115

AWS Big Data

MARCH 28, 2023

As organizations across the globe are modernizing their data platforms with data lakes on Amazon Simple Storage Service (Amazon S3), handling SCDs in data lakes can be challenging.

Data Lake 69

Data Lake Testing Snapshot Sales 69

Cloudera

FEBRUARY 16, 2021

In the previous blog post , we looked at some of the application development concepts for the Cloudera Operational Database (COD). In this blog post, we’ll see how you can use other CDP services with COD. The following image shows you how COD integrates within your enterprise data lifecycle. . Conclusion.

Machine Learning 81

Machine Learning Data Lake Enterprise Data Warehouse 81

Cloudera

JANUARY 18, 2022

As a result of this innovative data solution, the company helped customers while keeping its default rate low. . The bank also used its data lake to feed a real-time dashboard that tracked employee health which led to better support for employees. As a result of the pandemic, everyone is doing more online.

Data Lake 91

Data Lake Digital Transformation Data-driven Dashboards 91

Cloudera

SEPTEMBER 15, 2021

The algorithms are imperfect, but they will get better in time as they “learn” by processing more data. . Fast-changing Data. Data analytics at the edge also allow organizations to cope with another significant challenge. With analytics at the edge, researchers can adjust their work as new data comes in.

IoT 115

IoT Analytics Internet of Things Data Lake 115

Cloudera

JANUARY 13, 2021

UOB’s 12-week foundational learning and development programme — “Better U” —underscores its focus on ensuring digital proficiency and data analytics skills. Putting data at the heart of the organisation. The platform is built on a data lake that centralises data in UOB business units across the organisation.

Digital Transformation 56

Digital Transformation Data-driven Data Lake Big Data 56

IBM Big Data Hub

MAY 19, 2023

With high-speed file transfer, integrated services and cross-region offerings, IBM Cloud Object Storage allows you to leverage your data securely. In addition, it helps to reduce backup costs, provide permanent access to archived data, store data for cloud-native applications and create data lakes for big data analytics and AI.

Unstructured Data 81

Unstructured Data Data Processing Manufacturing Data Lake 81

IBM Big Data Hub

JANUARY 5, 2023

The first generation of data architectures represented by enterprise data warehouse and business intelligence platforms were characterized by thousands of ETL jobs, tables, and reports that only a small group of specialized data engineers understood, resulting in an under-realized positive impact on the business.

Data Quality 52

Data Quality Data Architecture Strategy Data Lake 52

IBM Big Data Hub

JUNE 8, 2022

A typical organization’s data landscape consists of a large number of data stores across workflows, business processes and business units, including but not limited to data warehouses, data marts, data lakes, ODS, cloud data stores, and CRM databases. The volume of data assets.

Data-driven 59

Data-driven Enterprise Data Governance Data Lake 59

BizAcuity

MAY 16, 2022

The more effectively a company uses data, the better it performs. As a data analytics company, we have been observing a trend among certain large enterprises who are looking for real-time data streaming for analytics. Data mining. Do let us know if you found the blog useful in the comments.

Business Intelligence 52

Business Intelligence Data mining Visualization Data Lake 52

Sisense

JULY 8, 2020

We live in a world of data: there’s more of it than ever before, in a ceaselessly expanding array of forms and locations. Dealing with Data is your window into the ways Data Teams are tackling the challenges of this new world to help their companies and their customers thrive. From ETL to ELT and beyond.

Data Warehouse 90

Data Warehouse Data Lake Data-driven Cost-Benefit 90

Andrew White

DECEMBER 9, 2019

And don’t start with a focus on domain specific data. See: Webinar Effective Data and Analytics Governance – Finally! Blog A Little Data Governance Goes a Long Way. I spoke with an IT software vendor about an aspect of data and analytics governance. Analytical quality and analytics.

Analytics 66

Analytics Data Lake Data Governance Metadata 66

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. AWS Glue released version 4.0 runtime ( 3.5

Testing 75

Testing Data Lake Cost-Benefit Data Integration 75

TDAN

MARCH 19, 2019

Various databases, plus one or more data warehouses, have been the state-of-the art data management infrastructure in companies for years. The emergence of various new concepts, technologies, and applications such as Hadoop, Tableau, R, Power BI, or Data Lakes indicate that changes are under way.

Management 84

Management Data Lake Data Warehouse Analytics 84

CDW Research Hub

JULY 27, 2021

Reduce the total cost of ownership of the data infrastructure. Build the foundation for a logical data warehouse or logical data lake. Maintain one consistent business data model across all consumers and reporting tools. Reuse analytical objects across multiple tools and consuming applications.

Data Warehouse 52

Data Warehouse Data Lake Data Architecture Consulting 52

Cloudera

JANUARY 24, 2022

Working with Cloudera, Keck created a data lake that eliminated manual data collection errors and gave visibility organization-wide. With advanced analytics, researchers and doctors are able to detect high-risk situations and take appropriate actions, such as patient and physician education.

Data Lake 64

Data Lake Risk Machine Learning Data Collection 64