DataKitchen

AUGUST 3, 2021

The data mesh design pattern breaks giant, monolithic enterprise data architectures into subsystems or domains, each managed by a dedicated team. First-generation – expensive, proprietary enterprise data warehouse and business intelligence platforms maintained by a specialized team drowning in technical debt.

Data Architecture 246

Data Architecture Data Lake Cost-Benefit Data Warehouse 246

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 93

Data Lake Data Warehouse Machine Learning Cost-Benefit 93

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

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

Smart Data Collective

MARCH 21, 2022

More case studies are added every day and give a clear hint – data analytics are all set to change, again! . Data Management before the ‘Mesh’. In the early days, organizations used a central data warehouse to drive their data analytics. This ensures 100% data control with the domains.

Management 67

Management Data Lake Uncertainty Data Warehouse 67

AWS Big Data

FEBRUARY 29, 2024

However, enterprise data generated from siloed sources combined with the lack of a data integration strategy creates challenges for provisioning the data for generative AI applications. As part of the transformation, the objects need to be treated to ensure data privacy (for example, PII redaction).

Data Governance 92

Data Governance Unstructured Data Metadata Data Lake 92

David Menninger's Analyst Perspectives

NOVEMBER 30, 2021

TIBCO is a large, independent cloud-computing and data analytics software company that offers integration, analytics, business intelligence and events processing software. It enables organizations to analyze streaming data in real time and provides the capability to automate analytics processes.

Analytics 175

Analytics Data Warehouse Business Intelligence Software 175

Jedox

OCTOBER 22, 2020

The term “data analytics” refers to the process of examining datasets to draw conclusions about the information they contain. Data analysis techniques enhance the ability to take raw data and uncover patterns to extract valuable insights from it. Data analytics is not new.

Data Analytics 69

Data Analytics Analytics Unstructured Data Data mining 69

AWS Big Data

MARCH 25, 2024

In this post, we discuss why data streaming is a crucial component of generative AI applications due to its real-time nature. In-context learning LLMs are trained with point-in-time data and have no inherent ability to access fresh data at inference time. For more information, refer to Dynamic Tables.

Data Lake 87

Data Lake Unstructured Data Management Modeling 87

AWS Big Data

DECEMBER 21, 2023

As the volume and complexity of analytics workloads continue to grow, customers are looking for more efficient and cost-effective ways to ingest and analyse data. OpenSearch Service is used for multiple purposes, such as observability, search analytics, consolidation, cost savings, compliance, and integration.

Analytics 93

Analytics IT Data Lake Visualization 93

CIO Business Intelligence

JULY 24, 2022

He has also been general manager technology with MyLife MyFinance and has held several roles with Me Bank during his five years with the financial institution. Herbert was responsible for data management and analytics capability. Prior to BankVic, Kuret was head of technology with Equipsuper for more than two years.

IT 98

IT Data Lake Digital Transformation Data Warehouse 98

Sisense

JULY 8, 2020

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. In recent years we’ve seen data become vastly more available to businesses. This has allowed companies to become more and more data driven in all areas of their business.

Data Warehouse 90

Data Warehouse Data Lake Data-driven Cost-Benefit 90

AWS Big Data

JANUARY 24, 2024

AWS-powered data lakes, supported by the unmatched availability of Amazon Simple Storage Service (Amazon S3), can handle the scale, agility, and flexibility required to combine different data and analytics approaches. For more information, refer to Amazon S3: Allows read and write access to objects in an S3 Bucket.

Snapshot 97

Snapshot Data Lake Metadata Optimization 97

DataKitchen

JANUARY 3, 2022

Their business unit colleagues ask an endless stream of urgent questions that require analytic insights. Business analysts must rapidly deliver value and simultaneously manage fragile and error-prone analytics production pipelines. Analytics Hub and Spoke. Teams under the CDO and CAO are sometimes separate from the CIO.

Business Analytics 245

Business Analytics Analytics Testing Dashboards 245

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 95

Data Warehouse Testing Data Lake Data-driven 95

CDW Research Hub

JULY 27, 2021

Data volumes are growing exponentially, and traditional, on-premises data warehouses are constrained, overly complex, and costly to scale. This enables organizations to connect to any data source and combine any type of data. Reduce the total cost of ownership of the data infrastructure.

Data Warehouse 52

Data Warehouse Data Lake Data Architecture Consulting 52

DataKitchen

AUGUST 27, 2021

DataOps has become an essential methodology in pharmaceutical enterprise data organizations, especially for commercial operations. Companies that implement it well derive significant competitive advantage from their superior ability to manage and create value from data.

Analytics 246

Analytics Sales Testing Cost-Benefit 246

AWS Big Data

DECEMBER 5, 2023

HR&A also realized about a 75% reduction in overall deployment and dashboard management time, which meant the consulting team could redirect their focus from manually analyzing data to helping clients interpret and strategically plan around the results. She helps customers architect data analytics solutions at scale on AWS.

Measurement 79

Measurement Dashboards Data Warehouse Analytics 79

CIO Business Intelligence

SEPTEMBER 12, 2022

Data from that surfeit of applications was distributed in multiple repositories, mostly traditional databases. Fazal instructed his IT team to collect every bit of data and methodically determine its use later, rather than lose “precious” data in the rush to build a massive data warehouse. “We

Data Warehouse 116

Data Warehouse Predictive Analytics Data Lake IoT 116

AWS Big Data

NOVEMBER 9, 2023

It allows users to write data transformation code, run it, and test the output, all within the framework it provides. dbt enables you to write SQL select statements, and then it manages turning these select statements into tables or views in Amazon Redshift.

Data Warehouse 102

Data Warehouse Testing Data Quality Reporting 102

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

DECEMBER 13, 2023

A CDC-based approach captures the data changes and makes them available in data warehouses for further analytics in real-time. usually a data warehouse) needs to reflect those changes in near real-time. This post showcases how to use streaming ingestion to bring data to Amazon Redshift.

Data Warehouse 95

Data Warehouse Snapshot Data Processing Management 95

IBM Big Data Hub

JANUARY 5, 2023

The right data architecture can help your organization improve data quality because it provides the framework that determines how data is collected, transported, stored, secured, used and shared for business intelligence and data science use cases. Reduce data duplication and fragmentation.

Data Quality 52

Data Quality Data Architecture Strategy Data Lake 52

IBM Big Data Hub

APRIL 25, 2023

To do so, Presto and Spark need to readily work with existing and modern data warehouse infrastructures. Now, let’s chat about why data warehouse optimization is a key value of a data lakehouse strategy. To effectively use raw data, it often needs to be curated within a data warehouse.

Optimization 57

Optimization Strategy Data Warehouse Cost-Benefit 57

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. The first diagram illustrates the architecture before using data sharing.

Testing 96

Testing Data Warehouse Metrics Cost-Benefit 96

CIO Business Intelligence

DECEMBER 1, 2022

Tapped to guide the company’s digital journey, as she had for firms such as P&G and Adidas, Kanioura has roughly 1,000 data engineers, software engineers, and data scientists working on a “human-centered model” to transform PepsiCo into a next-generation company. But there is more room to go.

Digital Transformation 144

Digital Transformation IoT Data-driven KPI 144

Jen Stirrup

MAY 5, 2020

Organizations need to recast storing their data. It is more than just some giant USB stick in the sky that’s going to store all of the data. It has a lot of services that you can use, such as Big Data analytics. You can also use Azure Data Lake storage as well, which is optimized for high-performance analytics.

Machine Learning 89

Machine Learning Data Science Data Lake Big Data 89

BizAcuity

JULY 13, 2021

In many cases, source data is captured in various databases and the need for data consolidation arises and typically it takes around 6-9 months to complete, and with a high budget in terms of provisioning for servers, either in cloud or on-premise, licenses for data warehouse platform, reporting system, ETL tools, etc.

Optimization 52

Optimization Marketing Analytics Data Warehouse 52

AWS Big Data

APRIL 20, 2023

Apache Spark is a popular framework that you can use to build applications for use cases such as ETL (extract, transform, and load), interactive analytics, and machine learning (ML). Amazon Redshift integration for Apache Spark helps developers seamlessly build and run Apache Spark applications on Amazon Redshift data.

Data Lake 73

Data Lake Data Warehouse Sales Data-driven 73

Sisense

APRIL 26, 2020

Read on to explore more about structured vs unstructured data, why the difference between structured and unstructured data matters, and how cloud data warehouses deal with them both. Structured vs unstructured data. However, both types of data play an important role in data analysis.

Unstructured Data 52

Unstructured Data Data Warehouse Structured Data Data mining 52

IBM Big Data Hub

JUNE 8, 2022

Ensuring data quality and access within an organization, while establishing and maintaining proper governance processes, is a major struggle for many organizations. Here are a few common data management challenges: Regulatory compliance on data use. Whether data protection regulations like GDPR, CCPA, HIPAA, etc.

Data-driven 58

Data-driven Enterprise Data Governance Data Lake 58

BizAcuity

MAY 16, 2022

Now, businesses, regardless of the industry, are leveraging data and Business Intelligence to stay ahead of the competition. In brief, business intelligence is about how well you leverage, manage and analyze business data. The more effectively a company uses data, the better it performs. Data mining.

Business Intelligence 52

Business Intelligence Data mining Visualization Data Lake 52

AWS Big Data

JANUARY 8, 2024

This is the first post to a blog series that offers common architectural patterns in building real-time data streaming infrastructures using Kinesis Data Streams for a wide range of use cases. In this post, we will review the common architectural patterns of two use cases: Time Series Data Analysis and Event Driven Microservices.

Analytics 109

Analytics IoT Data-driven Snapshot 109

Sisense

JANUARY 13, 2020

From a practical perspective, the computerization and automation of manufacturing hugely increase the data that companies acquire. And cloud data warehouses or data lakes give companies the capability to store these vast quantities of data. Making the changes work for manufacturing.

Manufacturing 52

Manufacturing Data Lake Big Data Data Warehouse 52

AWS Big Data

JUNE 6, 2023

Unless, of course, the rest of their data also resides in the Google Cloud. In this post we showcase how we used AWS Glue to move siloed digital analytics data, with inconsistent arrival times, to AWS S3 (our Data Lake) and our central data warehouse (DWH), Snowflake.

Analytics 56

Analytics Data Lake Testing Optimization 56

CIO Business Intelligence

SEPTEMBER 6, 2022

As a result, Pimblett now runs the organization’s data warehouse, analytics, and business intelligence. Establishing a clear and unified approach to data. Instead, says Pimblett, he and his data colleagues ask business managers, “Where do you think you can create value from data?

IT 98

IT Forecasting Data Lake Enterprise 98

CIO Business Intelligence

APRIL 6, 2022

Innovation should be encouraged and embraced, however, there is generally an unrecognized need to systematically manage the innovation process. While enterprises invest in innovation, key challenges such as successful sustenance, ROI realization, scaling and accelerating still remain. . Accelerate Innovation.

Experimentation 103

Experimentation Data Lake Uncertainty Enterprise 103