datapine

MAY 2, 2023

Table of Contents 1) Benefits Of Big Data In Logistics 2) 10 Big Data In Logistics Use Cases Big data is revolutionizing many fields of business, and logistics analytics is no exception. The complex and ever-evolving nature of logistics makes it an essential use case for big data applications. Did you know?

Big Data 275

Big Data Internet of Things Cost-Benefit Optimization 275

DataKitchen

OCTOBER 5, 2022

Observability is a methodology for providing visibility of every journey that data takes from source to customer value across every tool, environment, data store, team, and customer so that problems are detected and addressed immediately. to monitor your data operations. DataOps Industry Challenges. This call is from the CEO?his

Testing 182

Testing Risk Data Processing Statistics 182

datapine

SEPTEMBER 29, 2022

What Is Data Quality Management (DQM)? Data quality management is a set of practices that aim at maintaining a high quality of information. It goes all the way from the acquisition of data and the implementation of advanced data processes, to an effective distribution of data.

Data Quality 241

Data Quality Metrics Data-driven Management 241

DataKitchen

NOVEMBER 10, 2023

Extrinsic Control Deficit: Many of these changes stem from tools and processes beyond the immediate control of the data team. Unregulated ETL/ELT Processes: The absence of stringent data quality tests in ETL (Extract, Transform, Load) or ELT (Extract, Load, Transform) processes further exacerbates the problem.

Data Quality 145

Data Quality Testing Data Lake Data Integration 145

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

OCTOBER 23, 2024

response = client.create( key="test", value="Test value", description="Test description" ) print(response) print("nListing all variables.") variables = client.list() print(variables) print("nGetting the test variable.") Creating a test variable. Creating a test variable. Creating a test variable.

Interactive 114

Interactive Testing Data-driven Data Lake 114

Jen Stirrup

SEPTEMBER 30, 2021

They may also learn from evidence, but the data and the modelling fundamentally comes from humans in some way. Data Science – Data science is the field of study that combines domain expertise, programming skills, and knowledge of mathematics and statistics to extract meaningful insights from data. Credit: [link].

Business Intelligence 135

Business Intelligence Data mining Machine Learning Testing 135

AWS Big Data

NOVEMBER 27, 2024

The data in Amazon Redshift is transactionally consistent and updates are automatically and continuously propagated. Together with price-performance, Amazon Redshift offers capabilities such as serverless architecture, machine learning integration within your data warehouse and secure data sharing across the organization.

Data Warehouse 108

Data Warehouse Analytics Testing Modeling 108

DataKitchen

DECEMBER 20, 2020

Data-driven companies sense change through data analytics. Companies turn to their data organization to provide the analytics that stimulates creative problem-solving. Companies turn to their data organization to provide the analytics that stimulates creative problem-solving. – Leon C. Adapt or face decline.

Data-driven 147

Data-driven Manufacturing Data Architecture Data Analytics 147

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 126

Data Warehouse Testing Data Quality Reporting 126

Sisense

AUGUST 28, 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. What is data integrity?

Data Integration 101

Data Integration Testing Data Quality Data-driven 101

CIO Business Intelligence

JULY 5, 2022

What is the difference between business analytics and data analytics? Business analytics is a subset of data analytics. Data analytics is used across disciplines to find trends and solve problems using data mining , data cleansing, data transformation, data modeling, and more.

Business Analytics 136

Business Analytics Prescriptive Analytics Data mining Diagnostic Analytics 136

CIO Business Intelligence

JUNE 7, 2022

What is data analytics? Data analytics is a discipline focused on extracting insights from data. It comprises the processes, tools and techniques of data analysis and management, including the collection, organization, and storage of data. What are the four types of data analytics?

Data Analytics 135

Data Analytics Diagnostic Analytics Management Analytics 135

DataKitchen

OCTOBER 5, 2022

Observability is a methodology for providing visibility of every journey that data takes from source to customer value across every tool, environment, data store, team, and customer so that problems are detected and addressed immediately. to monitor your data operations. DataOps Industry Challenges. This call is from the CEO?his

Testing 130

Testing Risk Data Processing Statistics 130

AWS Big Data

JULY 18, 2024

The main driving factors include lower total cost of ownership, scalability, stability, improved ingestion connectors (such as Data Prepper , Fluent Bit, and OpenSearch Ingestion), elimination of external cluster managers like Zookeeper, enhanced reporting, and rich visualizations with OpenSearch Dashboards.

Dashboards 113

Dashboards Testing Data-driven Visualization 113

AWS Big Data

NOVEMBER 22, 2024

The need for streamlined data transformations As organizations increasingly adopt cloud-based data lakes and warehouses, the demand for efficient data transformation tools has grown. This approach helps in managing storage costs while maintaining the flexibility to analyze historical trends when needed.

Data Lake 100

Data Lake Data Warehouse Cost-Benefit Data Transformation 100

DataKitchen

OCTOBER 25, 2022

Observability is a methodology for providing visibility of every journey that data takes from source to customer value across every tool, environment, data store, team, and customer so that problems are detected and addressed immediately. Data journey observability is the first step in implementing DataOps.

Testing 130

Testing Data-driven Visualization Dashboards 130

CIO Business Intelligence

JANUARY 19, 2024

Data scientist is one of the hottest jobs in IT. Companies are increasingly eager to hire data professionals who can make sense of the wide array of data the business collects. Candidates for the exam are tested on ML, AI solutions, NLP, computer vision, and predictive analytics.

Data Science 126

Data Science Machine Learning Predictive Modeling Experimentation 126

Cloudera

DECEMBER 9, 2022

Cloudera has been providing enterprise support for Apache NiFi since 2015, helping hundreds of organizations take control of their data movement pipelines on premises and in the public cloud. Developers need to onboard new data sources, chain multiple data transformation steps together, and explore data as it travels through the flow.

Testing 105

Testing Cost-Benefit Interactive Visualization 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 86

Data Warehouse Data Transformation Testing Data Lake 86

AWS Big Data

DECEMBER 13, 2023

In addition to using native managed AWS services that BMS didn’t need to worry about upgrading, BMS was looking to offer an ETL service to non-technical business users that could visually compose data transformation workflows and seamlessly run them on the AWS Glue Apache Spark-based serverless data integration engine.

Metadata 111

Metadata Data Lake Visualization Data Transformation 111

Occam's Razor

OCTOBER 19, 2010

An expansive view of what it means to use data online, both from the type of data perspective and the kind of desired impact perspective. What is the first thing you want when you think about web analytics? Of course tools. What to do, where to start, what's cool. recommending tools for the complete web analytics 2.0 spectrum.

Analytics 136

Analytics Testing Measurement Optimization 136

AWS Big Data

JUNE 19, 2024

Amazon Redshift is a fast, scalable, secure, and fully managed cloud data warehouse that makes it simple and cost-effective to analyze all your data using standard SQL and your existing ETL (extract, transform, and load), business intelligence (BI), and reporting tools. All columns should masked for them.

Data Warehouse 114

Data Warehouse Testing Sales Structured Data 114

AWS Big Data

APRIL 12, 2023

We also share a Spark benchmark solution that suits all Amazon EMR deployment options, so you can replicate the process in your environment for your own performance test cases. The solution uses the TPC-DS dataset and unmodified data schema and table relationships, but derives queries from TPC-DS to support the SparkSQL test cases.

Testing 101

Testing Big Data Metadata Optimization 101

Cloudera

OCTOBER 19, 2021

Airflow has been adopted by many Cloudera Data Platform (CDP) customers in the public cloud as the next generation orchestration service to setup and operationalize complex data pipelines. Making the most commonly used as readily available as possible is critical to reduce development friction. .

Data Transformation 123

Data Transformation Interactive Machine Learning Testing 123

AWS Big Data

JULY 26, 2023

To grow the power of data at scale for the long term, it’s highly recommended to design an end-to-end development lifecycle for your data integration pipelines. The following are common asks from our customers: Is it possible to develop and test AWS Glue data integration jobs on my local laptop?

Data Integration 95

Data Integration Snapshot Testing Visualization 95

Cloudera

MARCH 14, 2023

We just announced the general availability of Cloudera DataFlow Designer , bringing self-service data flow development to all CDP Public Cloud customers. In this blog post we will put these capabilities in context and dive deeper into how the built-in, end-to-end data flow life cycle enables self-service data pipeline development.

Testing 90

Testing Publishing Metadata Interactive 90

AWS Big Data

AUGUST 1, 2024

However, you might face significant challenges when planning for a large-scale data warehouse migration. This will enable right-sizing the Redshift data warehouse to meet workload demands cost-effectively. Identify all upstream and downstream applications, as well as business processes that rely on the data warehouse.

Data Warehouse 113

Data Warehouse KPI Optimization Cost-Benefit 113

AWS Big Data

NOVEMBER 15, 2023

It seamlessly consolidates data from various data sources within AWS, including AWS Cost Explorer (and forecasting with Cost Explorer ), AWS Trusted Advisor , and AWS Compute Optimizer. Overview of the BMW Cloud Data Hub At the BMW Group, Cloud Data Hub (CDH) is the central platform for managing company-wide data and data solutions.

Dashboards 111

Dashboards Analytics Metadata Data Warehouse 111

AWS Big Data

DECEMBER 16, 2024

For each service, you need to learn the supported authorization and authentication methods, data access APIs, and framework to onboard and test data sources. This approach simplifies your data journey and helps you meet your security requirements. Choose Add data. For Database , enter your database name.

Visualization 88

Visualization Data Processing Testing Publishing 88

AWS Big Data

AUGUST 9, 2024

AWS offers Redshift Test Drive to validate whether the configuration chosen for Amazon Redshift is ideal for your workload before migrating the production environment. It represents a significant decrease in the delivery time of our critical data analytics processes. We removed the DC2 cluster and completed the migration.

Data Lake 111

Data Lake Analytics Data Warehouse Data-driven 111

Smart Data Collective

APRIL 29, 2020

What is data management? Data management can be defined in many ways. The techniques for managing organisational data in a standardised approach that minimises inefficiency. Extraction, Transform, Load (ETL). Data transformation. Data analytics and visualisation. Microsoft Azure.

Management 88

Management Data Warehouse Digital Transformation Dashboards 88

AWS Big Data

AUGUST 9, 2023

The advent of rapid adoption of serverless data lake architectures—with ever-growing datasets that need to be ingested from a variety of sources, followed by complex data transformation and machine learning (ML) pipelines—can present a challenge. Disable the rules after testing to avoid repeated messages.

Data Lake 98

Data Lake Metrics Testing Cost-Benefit 98

AWS Big Data

AUGUST 26, 2024

Duplicating data from a production database to a lower or lateral environment and masking personally identifiable information (PII) to comply with regulations enables development, testing, and reporting without impacting critical systems or exposing sensitive customer data. 16 10.2.10.0/24 24 AWS Glue account 10.1.0.0/16

Visualization 115

Visualization Metadata Data Transformation Testing 115

Cloudera

OCTOBER 13, 2020

CDP Machine Learning: a kubernetes-based service that allows data scientists to deploy collaborative workspaces with secure, self-service access to enterprise data. Predict – Data Engineering (Apache Spark). 3) Data Visualization is in Tech Preview on AWS and Azure. New Services. Learn More, Keep in Touch.

Data Warehouse 103

Data Warehouse Machine Learning Visualization Data Lake 103

AWS Big Data

OCTOBER 18, 2023

Spark SQL is an Apache Spark module for structured data processing. To look for fraud, market manipulation, insider trading, and abuse, FINRA’s technology group has developed a robust set of big data tools in the AWS Cloud to support these activities. Starting from version 1.2.0, Apache Spark has supported queries written in HiveQL.

Big Data 104

Big Data Data Processing Interactive Testing 104

AWS Big Data

FEBRUARY 26, 2024

When you start the process of designing your data model for Amazon Keyspaces, it’s essential to possess a comprehensive understanding of your access patterns, similar to the approach used in other NoSQL databases. It empowers businesses to explore and gain insights from large volumes of data quickly.

Dashboards 84

Dashboards Testing Metrics Optimization 84