erwin

AUGUST 15, 2022

For NoSQL, data lakes, and data lake houses—data modeling of both structured and unstructured data is somewhat novel and thorny. This blog is an introduction to some advanced NoSQL and data lake database design techniques (while avoiding common pitfalls) is noteworthy. Data modeling basics.

Data Lake 52

Data Lake Modeling Unstructured Data Data Warehouse 52

AWS Big Data

SEPTEMBER 22, 2023

At Stitch Fix, we have been powered by data science since its foundation and rely on many modern data lake and data processing technologies. In our infrastructure, Apache Kafka has emerged as a powerful tool for managing event streams and facilitating real-time data processing.

Management 101

Management Metrics Cost-Benefit Data Lake 101

Cloudera

JUNE 16, 2022

The ability to perform analytics on data as it is created and collected (a.k.a. real-time data streams) and generate immediate insights for faster decision making provides a competitive edge for organizations. . CSP was recently recognized as a leader in the 2022 GigaOm Radar for Streaming Data Platforms report.

Data Lake 85

Data Lake Manufacturing Metadata Dashboards 85

Cloudera

JANUARY 21, 2021

Does your organization’s success depend on immediate delivery of new reports, applications, or projects? While cloud-native, point-solution data warehouse services may serve your immediate business needs, there are dangers to the corporation as a whole when you do your own IT this way. Do you need faster time to value?

Data Lake 93

Data Lake Data Warehouse IT Analytics 93

AWS Big Data

MAY 30, 2023

Customers have been using data warehousing solutions to perform their traditional analytics tasks. Recently, data lakes have gained lot of traction to become the foundation for analytical solutions, because they come with benefits such as scalability, fault tolerance, and support for structured, semi-structured, and unstructured datasets.

Data Lake 79

Data Lake Data Analytics Analytics Data Processing 79

CIO Business Intelligence

MARCH 22, 2022

Most organizations have come to understand the importance of being data-driven. To compete in a digital economy, it’s essential to base decisions and actions on accurate data, both real-time and historical. But the sheer volume of the world’s data is expected to nearly triple between 2020 and 2025 to a whopping 180 zettabytes.

Analytics 106

Analytics Key Performance Indicator Data Warehouse Data-driven 106

AWS Big Data

OCTOBER 18, 2023

Amazon Redshift is a fast, fully managed, petabyte-scale data warehouse that provides the flexibility to use provisioned or serverless compute for your analytical workloads. Modern analytics is much wider than SQL-based data warehousing. Modern analytics is much wider than SQL-based data warehousing. Fault tolerance is built in.

Analytics 94

Analytics Data Warehouse Testing Dashboards 94

AWS Big Data

MARCH 7, 2023

It covers how to use a conceptual, logical architecture for some of the most popular gaming industry use cases like event analysis, in-game purchase recommendations, measuring player satisfaction, telemetry data analysis, and more. Flexible and easy to use – The solutions should provide less restrictive, easy-to-access, and ready-to-use data.

Analytics 70

Analytics Data Warehouse Data Lake Metadata 70

CIO Business Intelligence

JANUARY 10, 2024

Optimizing cloud investments requires close collaboration with the rest of the business to understand current and future needs, building effective FinOps teams, partnering with providers, and ongoing monitoring of key performance metrics. FinOps teams are critical to success, says Vunvulea. Today, he says, they operate more accurately.

Cost-Benefit 118

Cost-Benefit Measurement Optimization Metrics 118

AWS Big Data

APRIL 19, 2023

Many customers run big data workloads such as extract, transform, and load (ETL) on Apache Hive to create a data warehouse on Hadoop. Solution overview In our example, we use Apache Oozie, which schedules Apache Hive jobs as actions to collect and process data on a daily basis. Python packages: sqlparse==0.4.2 jproperties==2.1.1

Metadata 78

Metadata Testing Data Lake Consulting 78

CIO Business Intelligence

APRIL 6, 2022

While enterprises invest in innovation, key challenges such as successful sustenance, ROI realization, scaling and accelerating still remain. . They are nurturing agile and elite ecosystems in an effort to outpace the competition and deliver tangible returns on the innovation investments. . Accelerate Innovation. The Differentiators.

Experimentation 92

Experimentation Data Lake Uncertainty Enterprise 92

BI-Survey

AUGUST 21, 2020

Data warehousing is getting on in years. However, data warehousing and BI applications are only considered moderately successful. Advanced analytics and new ways of working with data also create new requirements that surpass the traditional concepts. Can the basic nature of the data be proactively improved?

Data Warehouse 98

Data Warehouse Data Lake Data Governance Data Architecture 98

Cloudera

DECEMBER 21, 2020

In this blog we will take you through a persona-based data adventure, with short demos attached, to show you the A-Z data worker workflow expedited and made easier through self-service, seamless integration, and cloud-native technologies. In our data adventure we assume the following: . Company data exists in the data lake.

Dashboards 97

Dashboards Visualization Data Warehouse Data Lake 97

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 82

Enterprise Data Warehouse Snapshot Cost-Benefit 82

Jedox

JANUARY 13, 2023

Increasing efficiency in an organization’s planning, budgeting, and forecasting processes is a key component of financial planning software, according to Gartner. Efficient implementation is a key differentiator for enterprises looking to achieve quick time to value. Configurable models. Implementation strategy.

Software 52

Software Finance Forecasting Data Lake 52

Cloudera

FEBRUARY 18, 2022

“I’d go as far as to say that today, soft skills can spell the difference between success and failure between workers and their employer, and in the time of the great resignation that impact is even greater.” We do this by being honest and vulnerable ourselves and living core qualities through key touchpoints.

Data Lake 84

Data Lake Uncertainty Dashboards Optimization 84

erwin

JUNE 7, 2022

Designing databases for data warehouses or data marts is intrinsically much different than designing for traditional OLTP systems. Accordingly, data modelers must embrace some new tricks when designing data warehouses and data marts. Data modeling for the cloud: good database design means “right size” and savings.

Data Warehouse 52

Data Warehouse Modeling Sales Data Lake 52

Cloudera

AUGUST 28, 2020

To continue where we left off, as industry players continue to shift toward a more 5G centric network, how is 5G impacting the industry from a data perspective? Augmented and virtual reality services are also now possible and will really be brought to life with 5G. 5G and IoT are going to drive an explosion in data.

IoT 109

IoT Machine Learning B2B Testing 109

Cloudera

JANUARY 11, 2021

Requests to Central IT for data warehousing services can take weeks or months to deliver. In data-driven organizations, to fulfill its charter to democratize data and provide on-demand, quality computing services in a secure, compliant environment, IT must replace legacy approaches and update technologies. billion dollars.’.

Data Warehouse 61

Data Warehouse Data Lake Cost-Benefit Machine Learning 61

IBM Big Data Hub

DECEMBER 16, 2022

An enterprise data catalog does all that a library inventory system does – namely streamlining data discovery and access across data sources – and a lot more. For example, data catalogs have evolved to deliver governance capabilities like managing data quality and data privacy and compliance.

Metadata 52

Metadata Data Quality Data-driven Data Governance 52

Domino Data Lab

JUNE 15, 2021

These companies often undertake large data science efforts in order to shift from “data-driven” to “model-driven” operations, and to provide model-underpinned insights to the business. The typical data science journey for a company starts with a small team that is tasked with a handful of specific problems.

Modeling 69

Modeling Data Science Data-driven Data Warehouse 69

Cloudera

NOVEMBER 12, 2020

Cloud has given us hope, with public clouds at our disposal we now have virtually infinite resources, but they come at a different cost – using the cloud means we may be creating yet another series of silos, which also creates unmeasurable new risks in security and traceability of our data. Key areas of concern are: .

Data Warehouse 101

Data Warehouse Reporting Risk Cost-Benefit 101

AWS Big Data

JUNE 29, 2023

Amazon Kinesis Data Analytics makes it easy to transform and analyze streaming data in real time. In this post, we discuss why AWS recommends moving from Kinesis Data Analytics for SQL Applications to Amazon Kinesis Data Analytics for Apache Flink to take advantage of Apache Flink’s advanced streaming capabilities.

Data Analytics 73

Data Analytics Analytics IoT Data Lake 73

Cloudera

FEBRUARY 16, 2022

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. Each project consists of a declarative series of steps or operations that define the data science workflow.

Machine Learning 82

Machine Learning Modeling Metadata Recreation/Entertainment 82

CIO Business Intelligence

MARCH 2, 2023

The company measures the success of these efforts by business outcomes, not the success of the automation itself, he adds. It’s become one of the key levers in the client experience, and it plays different roles throughout the lifecycle of that change,” says Sippel. million consumers.

Data Lake 143

Data Lake Forecasting B2B Optimization 143

Domino Data Lab

AUGUST 8, 2019

Paco Nathan ‘s latest monthly article covers Sci Foo as well as why data science leaders should rethink hiring and training priorities for their data science teams. In this episode I’ll cover themes from Sci Foo and important takeaways that data science teams should be tracking. Introduction. Ever heard of it before?

Data Science 71

Data Science Machine Learning Data Governance Statistics 71

AWS Big Data

OCTOBER 25, 2023

Unstructured data is information that doesn’t conform to a predefined schema or isn’t organized according to a preset data model. Text, images, audio, and videos are common examples of unstructured data. After decades of digitizing everything in your enterprise, you may have an enormous amount of data, but with dormant value.

Unstructured Data 117

Unstructured Data Metadata Management Analytics 117

datapine

AUGUST 29, 2022

The saying “knowledge is power” has never been more relevant, thanks to the widespread commercial use of big data and data analytics. The rate at which data is generated has increased exponentially in recent years. Companies, both big and small, are seeking the finest ways to leverage their data into a competitive advantage.

Big Data 263

Big Data Data Analytics Analytics Data mining 263

Alation

MARCH 29, 2021

How data catalogs with search & discovery help users. To keep up, more businesses have shifted toward data-driven decision making. According to a NewVantage Partners Report , 96% of executives indicate that their organization aspires to a data-driven culture, while only 24% report success.

Metadata 59

Metadata Data-driven Enterprise Machine Learning 59

Alation

FEBRUARY 13, 2020

While he successfully built a culture of innovation, he missed a key ingredient, customer demand. It requires organizations to adopt a scientific mindset of testing and iteration to find the truth, rather than using data to support a predetermined path. Sustainable innovation is often customer-centric if not customer-led. The reason?

Digital Transformation 59

Digital Transformation Insurance Data-driven Machine Learning 59

BI-Survey

NOVEMBER 23, 2021

The existence of data silos is nothing new. Data-producing applications were once isolated systems. The transactional data was stored in isolated data sets and initially served only one purpose, namely, to document the transaction that had taken place. Over time, enterprises realized that data is worth more.

Digital Transformation 52

Digital Transformation Data Warehouse Data Lake Data-driven 52

BI-Survey

JANUARY 15, 2023

Data architecture is a topic that is as relevant today as ever. It is widely regarded as a matter for data engineers, not business domain experts. Statements from countless interviews with our customers reveal that the data warehouse is seen as a “black box” by many and understood by few business users. But is it really?

Data Warehouse 52

Data Warehouse IT Data Architecture Measurement 52

erwin

AUGUST 31, 2023

Q: Is data modeling cool again? In today’s fast-paced digital landscape, data reigns supreme. The data-driven enterprise relies on accurate, accessible, and actionable information to make strategic decisions and drive innovation. A: It always was and is getting cooler!!

Data-driven 98

Data-driven Modeling Enterprise Structured Data 98