AWS Big Data

DECEMBER 5, 2023

This frees up our local computer space, greatly automates the survey cleaning and analysis step, and allows our clients to easily access the data results. This cut down significantly on analytical turnaround times. The first step in this process is mapping the digital divide.

Measurement 80

Measurement Dashboards Data Warehouse Analytics 80

AWS Big Data

OCTOBER 27, 2023

Data integration is the foundation of robust data analytics. It encompasses the discovery, preparation, and composition of data from diverse sources. In the modern data landscape, accessing, integrating, and transforming data from diverse sources is a vital process for data-driven decision-making.

Analytics 95

Analytics Visualization Data Integration Cost-Benefit 95

AWS Big Data

NOVEMBER 9, 2023

Building a data platform involves various approaches, each with its unique blend of complexities and solutions. In this post, we delve into a case study for a retail use case, exploring how the Data Build Tool (dbt) was used effectively within an AWS environment to build a high-performing, efficient, and modern data platform.

Data Warehouse 104

Data Warehouse Testing Data Quality Reporting 104

DataKitchen

JULY 27, 2023

While working in Azure with our customers, we have noticed several standard Azure tools people use to develop data pipelines and ETL or ELT processes. We counted ten ‘standard’ ways to transform and set up batch data pipelines in Microsoft Azure. You can use it for big data analytics and machine learning workloads.

Machine Learning 130

Machine Learning Cost-Benefit Data Transformation Testing 130

AWS Big Data

APRIL 30, 2024

This reduces the time and effort you need to learn, build, and run data integration jobs using AWS Glue data integration engines. For example, you can ask Amazon Q Developer to generate a complete extract, transform, and load (ETL) script or code snippet for individual ETL operations.

Data Integration 102

Data Integration Data Lake Data Warehouse Software 102

Jet Global

FEBRUARY 23, 2024

Data mapping is essential for integration, migration, and transformation of different data sets; it allows you to improve your data quality by preventing duplications and redundancies in your data fields. Data mapping helps standardize, visualize, and understand data across different systems and applications.

Data Warehouse 52

Data Warehouse Reporting Data Transformation Sales 52

AWS Big Data

NOVEMBER 29, 2023

dbt is an open source, SQL-first templating engine that allows you to write repeatable and extensible data transforms in Python and SQL. dbt is predominantly used by data warehouses (such as Amazon Redshift ) customers who are looking to keep their data transform logic separate from storage and engine.

Data Lake 102

Data Lake Management Metrics Data Warehouse 102

AWS Big Data

DECEMBER 21, 2023

The data volume is in double-digit TBs with steady growth as business and data sources evolve. smava’s Data Platform team faced the challenge to deliver data to stakeholders with different SLAs, while maintaining the flexibility to scale up and down while staying cost-efficient.

Data Lake 88

Data Lake Data Warehouse Data-driven B2B 88

AWS Big Data

SEPTEMBER 19, 2023

However, our legacy data warehouse-based solution was not equipped for this challenge. However, with a minimum data freshness of 10 minutes, this architecture inherently didn’t align with the near real-time fraud detection use case. Amazon DynamoDB is another data source for our Streaming 2.0

Analytics 78

Analytics Risk Big Data Machine Learning 78

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 83

Enterprise Data Warehouse Data Lake Optimization 83

Jet Global

MARCH 14, 2024

Microsoft recently introduced a comprehensive analytics solution for its enterprise customers, Microsoft Fabric. The solution offers data movement, data science, real-time analytics, and business intelligence within a single platform. Or does it?

Analytics 52

Analytics Management Reporting Enterprise 52

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

CIO Business Intelligence

FEBRUARY 16, 2023

The company’s orthodontics business, for instance, makes heavy use of image processing to the point that unstructured data is growing at a pace of roughly 20% to 25% per month. For example, imaging data can be used to show patients how an aligner will change their appearance over time. “It The offensive side?

Unstructured Data 105

Unstructured Data Data Lake Prescriptive Analytics Digital Transformation 105

Cloudera

OCTOBER 7, 2022

We’re excited to announce the general availability of the open source adapters for dbt for all the engines in CDP — Apache Hive , Apache Impala , and Apache Spark, with added support for Apache Livy and Cloudera Data Engineering. The Open Data Lakehouse . Cloudera builds dbt adaptors for all engines in the open data lakehouse.

Data Warehouse 80

Data Warehouse Data Transformation Testing Data Lake 80

AWS Big Data

SEPTEMBER 6, 2023

Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. With Amazon Redshift, you can analyze all your data to derive holistic insights about your business and your customers. You can also schedule stored procedures to automate data processing on Amazon Redshift.

Data Warehouse 95

Data Warehouse Insurance Statistics Software 95

AWS Big Data

MARCH 16, 2023

Amazon Redshift is a fully managed data warehouse service that tens of thousands of customers use to manage analytics at scale. Together with price-performance , Amazon Redshift enables you to use your data to acquire new insights for your business and customers while keeping costs low.

Data Warehouse 52

Data Warehouse Testing Snapshot Modeling 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 85

Data Warehouse Machine Learning Data Integration Data-driven 85

CDW Research Hub

OCTOBER 20, 2020

Snowflake is a modern cloud data platform that boasts instant elasticity, secure data sharing and per-second pricing across multiple clouds. Its ability to natively load and use SQL to query semi-structured and structured data within a single system simplifies your data engineering.

Dashboards 72

Dashboards Reporting Data Warehouse Structured Data 72

Jet Global

MAY 1, 2023

Introduction Why should I read the definitive guide to embedded analytics? But many companies fail to achieve this goal because they struggle to provide the reporting and analytics users have come to expect. The Definitive Guide to Embedded Analytics is designed to answer any and all questions you have about the topic.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52

Cloudera

JULY 21, 2022

As creators and experts in Apache Druid, Rill understands the data store’s importance as the engine for real-time, highly interactive analytics. Rill provides pre-built connectors along with a front-end purpose-built for analyzing data in Druid. Data is made queryable in real time. Cloudera Data Warehouse).

Metrics 84

Metrics Slice and Dice Data Warehouse Dashboards 84

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

Smart Data Collective

APRIL 29, 2020

What is data management? Data management can be defined in many ways. The extraction of raw data, transforming to a suitable format for business needs, and loading into a data warehouse. Data transformation. Data analytics and visualisation.

Management 84

Management Data Warehouse Digital Transformation Dashboards 84

Cloudera

APRIL 12, 2021

The United States Veterans Administration (VA) over the last decade underwent a massive enterprise-wide IT transformation, eliminating its fragmented shadow IT and adopting a centralized system capable of supporting the agency’s 400,000 employees and more effectively utilizing its $240 billion-plus annual budget.

Enterprise 52

Enterprise IT Digital Transformation Data Warehouse 52

Jet Global

NOVEMBER 7, 2023

The Challenges of Extracting Enterprise Data Currently, various use cases require data extraction from your OCA ERP, including data warehousing, data harmonization, feeding downstream systems for analytical or operational purposes, leveraging data mining, predictive analysis, and AI-driven or augmented BI disciplines.

Enterprise 52

Enterprise Data Warehouse Operational Reporting Reporting 52

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 85

Data Lake Data Architecture Metadata Data Warehouse 85

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. What Is Data Quality Management (DQM)? But first, let’s define what data quality actually is. With a shocking 2.5

Data Quality 241

Data Quality Metrics Data-driven Management 241

Jet Global

MAY 6, 2024

This untapped potential suggests a significant opportunity for those willing to embrace AI and gain a competitive edge through intelligent automation and data-driven financial insights. These tools excel at data integration, consolidating information from various financial systems (ERP, CRM, legacy) into a central hub.

Finance 52

Finance Reporting Data Transformation Optimization 52

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

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. Note that you may have multiple projects as well.

Data Lake 83

Data Lake Data Transformation Cost-Benefit Data-driven 83

IBM Big Data Hub

OCTOBER 16, 2023

It includes processes that trace and document the origin of data, models and associated metadata and pipelines for audits. In other words, instead of training numerous models on labeled, task-specific data, it’s now possible to pre-train one big model built on a transformer and then, with additional fine-tuning, reuse it as needed.

Risk 78

Risk Modeling Management Metadata 78

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 157

Testing Dashboards Measurement Experimentation 157

Jet Global

APRIL 24, 2024

In the rapidly-evolving world of embedded analytics and business intelligence, one important question has emerged at the forefront: How can you leverage artificial intelligence (AI) to enhance your data analysis? How does AI impact analytics and how do you get started? Forget the one-size-fits-all approach.

Business Intelligence 52

Business Intelligence Dashboards Software Reporting 52

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 . 1 2008 7009728.

Snapshot 90

Snapshot Data Warehouse Machine Learning Cost-Benefit 90

FineReport

APRIL 21, 2024

In today’s data-driven landscape, businesses are constantly seeking innovative solutions to harness the power of analytics effectively. Embedded BI tools have emerged as a transformative force, seamlessly integrating analytical capabilities directly into existing software applications.

Dashboards 52

Dashboards Visualization Interactive Business Intelligence 52

Ontotext

FEBRUARY 12, 2024

For large enterprises, data mesh distributes data ownership and reduces dependencies between services. This promotes data autonomy and enables decision-making about data domains without centralized gatekeepers. What does data mesh do that other approaches can’t? What does data mesh do that other approaches can’t?

Data-driven 59

Data-driven Data Lake Data Quality Business Objectives 59

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 76

Data Lake Data Warehouse Data Architecture Reporting 76

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 91

Data Processing Data Warehouse Enterprise Visualization 91