datapine

SEPTEMBER 29, 2022

He/she assists the organization by providing clarity and insight into advanced data technology solutions. As quality issues are often highlighted with the use of dashboard software , the change manager plays an important role in the visualization of data quality. Here, it all comes down to the data transformation error rate.

Data Quality 241

Data Quality Metrics Data-driven Management 241

DataKitchen

OCTOBER 25, 2022

He thinks he can sell his boss and the CEO on this idea, but his pitch won’t go over well when they still have more than six major data errors every month. DataOps Observability Starts with Data Journeys. Jason considers his dashboard idea but quickly realizes the complexity of building such a system.

Testing 130

Testing Data-driven Visualization Dashboards 130

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 125

Business Analytics Prescriptive Analytics Data mining Diagnostic Analytics 125

Cloudera

JULY 21, 2022

Cloudera users can securely connect Rill to a source of event stream data, such as Cloudera DataFlow , model data into Rill’s cloud-based Druid service, and share live operational dashboards within minutes via Rill’s interactive metrics dashboard or any connected BI solution. Cloudera Data Warehouse). Apache Hive.

Metrics 84

Metrics Slice and Dice Data Warehouse Dashboards 84

CIO Business Intelligence

JUNE 7, 2022

Data analytics draws from a range of disciplines — including computer programming, mathematics, and statistics — to perform analysis on data in an effort to describe, predict, and improve performance. What are the four types of data analytics?

Data Analytics 128

Data Analytics Diagnostic Analytics Management Analytics 128

AWS Big Data

MARCH 3, 2023

Tricentis is the global leader in continuous testing for DevOps, cloud, and enterprise applications. Speed changes everything, and continuous testing across the entire CI/CD lifecycle is the key. Tricentis instills that confidence by providing software tools that enable Agile Continuous Testing (ACT) at scale.

Software 52

Software Data Lake Testing Cost-Benefit 52

AWS Big Data

OCTOBER 11, 2023

Key performance indicators (KPIs) of interest for a call center from a near-real-time platform could be calls waiting in the queue, highlighted in a performance dashboard within a few seconds of data ingestion from call center streams. Visualize KPIs of call center performance in near-real time through OpenSearch Dashboards.

Management 103

Management Metadata Analytics Dashboards 103

Jen Stirrup

SEPTEMBER 30, 2021

Before we dive in, let’s define strands of AI, Machine Learning and Data Science: Business intelligence (BI) leverages software and services to transform data into actionable insights that inform an organization’s strategic and tactical business decisions. Once the model has been trained, it will need to be tested.

Business Intelligence 135

Business Intelligence Data mining Machine Learning Testing 135

AWS Big Data

APRIL 5, 2023

Showpad built new customer-facing embedded dashboards within Showpad eOSTM and migrated its legacy dashboards to Amazon QuickSight , a unified BI service providing modern interactive dashboards, natural language querying, paginated reports, machine learning (ML) insights, and embedded analytics at scale.

Dashboards 52

Dashboards Reporting Cost-Benefit Visualization 52

AWS Big Data

JUNE 20, 2023

Kinesis Data Firehose is a fully managed service for delivering near-real-time streaming data to various destinations for storage and performing near-real-time analytics. You can perform analytics on VPC flow logs delivered from your VPC using the Kinesis Data Firehose integration with Datadog as a destination.

Dashboards 83

Dashboards Visualization Metrics Data Transformation 83

Smart Data Collective

APRIL 29, 2020

The techniques for managing organisational data in a standardised approach that minimises inefficiency. Extraction, Transform, Load (ETL). The extraction of raw data, transforming to a suitable format for business needs, and loading into a data warehouse. Data transformation. Amazon Web Services.

Management 84

Management Data Warehouse Digital Transformation Dashboards 84

AWS Big Data

NOVEMBER 13, 2023

Consequently, there was a fivefold rise in data integrations and a fivefold increase in ad hoc queries submitted to the Redshift cluster. Also, over time the number of BI dashboards (both scheduled and live) increased, which contributed to more queries being submitted to the Redshift cluster.

Data Warehouse 90

Data Warehouse Data Lake Analytics Data Science 90

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 71

Data Integration Snapshot Testing Visualization 71

AWS Big Data

FEBRUARY 6, 2023

Amazon QuickSight dashboards showcase the results from the analyzer. With QuickSight, you can visualize YARN log data and conduct analysis against the datasets generated by pre-built dashboard templates and a widget. This step creates datasets on QuickSight dashboards in your AWS target account. Choose Delete.

Dashboards 74

Dashboards Optimization Data Lake Cost-Benefit 74

AWS Big Data

MARCH 16, 2023

A source of unpredictable workloads is dbt Cloud , which SafetyCulture uses to manage data transformations in the form of models. Whenever models are created or modified, a dbt Cloud CI job is triggered to test the models by materializing the models in Amazon Redshift. Refer to Connect dbt Cloud to Redshift for setup steps.

Data Warehouse 52

Data Warehouse Testing Snapshot Modeling 52

Jet Global

FEBRUARY 23, 2024

This field guide to data mapping will explore how data mapping connects volumes of data for enhanced decision-making. Why Data Mapping is Important Data mapping is a critical element of any data management initiative, such as data integration, data migration, data transformation, data warehousing, or automation.

Data Warehouse 52

Data Warehouse Reporting Data Transformation Sales 52

Cloudera

FEBRUARY 8, 2021

Simple, drag-and-drop building of dashboards and apps with Cloudera Data Visualization. Stock Data – for pulling the stock data, I used alpha vantage service (free version). Next step is to create our table in which the data will be stored in our database. Now, let’s start testing our model!

Machine Learning 72

Machine Learning Statistics Modeling Dashboards 72

AWS Big Data

MAY 25, 2023

Data transformation plays a pivotal role in providing the necessary data insights for businesses in any organization, small and large. To gain these insights, customers often perform ETL (extract, transform, and load) jobs from their source systems and output an enriched dataset.

Reporting 68

Reporting Metrics Optimization Data Lake 68

Sisense

DECEMBER 12, 2019

Will every department need access to BI and dashboards? Executive dashboards : BI access is limited to the C-level, providing execs with a real-time, big-picture look at company performance. A bright, shiny BI tool that’s perfect for creating beautiful visual reports might be a dud when it comes to tackling complex data.

Business Intelligence 88

Business Intelligence Software Data-driven Visualization 88

AWS Big Data

JUNE 29, 2023

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. View the stream data. Transform and enrich the data. Manipulate the data with Python.

Data Analytics 73

Data Analytics Analytics IoT Data Lake 73

AWS Big Data

NOVEMBER 16, 2023

Building a starter version of anything can often be straightforward, but building something with enterprise-grade scale, security, resiliency, and performance typically requires knowledge of and adherence to battle-tested best practices, and using the right tools and features in the right scenario. Data Vault 2.0

Enterprise 83

Enterprise Data Warehouse Data Lake Optimization 83

Jet Global

MAY 1, 2023

Their dashboards were visually stunning. In turn, end users were thrilled with the bells and whistles of charts, graphs, and dashboards. As rich, data-driven user experiences are increasingly intertwined with our daily lives, end users are demanding new standards for how they interact with their business data.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52

O'Reilly on Data

OCTOBER 19, 2021

If you ask an engineer to show how they operate the application in production, they will likely show containers and operational dashboards—not unlike any other software service. The applications must be integrated to the surrounding business systems so ideas can be tested and validated in the real world in a controlled manner.

IT 346

IT Testing Experimentation Software 346

Alation

JANUARY 17, 2023

As data science is growing in popularity and importance , if your organization uses data science, you’ll need to pay more attention to picking the right tools for this. An example of a data science tool is Dataiku. Business Intelligence Tools: Business intelligence (BI) tools are used to visualize your data.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Transformation Business Intelligence 52

Alation

OCTOBER 27, 2022

Few actors in the modern data stack have inspired the enthusiasm and fervent support as dbt. This data transformation tool enables data analysts and engineers to transform, test and document data in the cloud data warehouse. But what does this mean from a practitioner perspective?

Metrics 52

Metrics Dashboards Sales Reporting 52

O'Reilly on Data

JANUARY 17, 2023

Upload your data, click through a workflow, walk away. If you’re a professional data scientist, you already have the knowledge and skills to test these models. That takes us to a conspicuous omission from that list of roles: the data scientists who focused on building basic models. Get your results in a few hours.

Machine Learning 325

Machine Learning Predictive Modeling Software Modeling 325

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 84

Data Lake Data Architecture Metadata Data Warehouse 84

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 77

Data Lake Data Warehouse Data Architecture Reporting 77

Alation

OCTOBER 28, 2021

This, in turn, empowers data leaders to better identify and develop new revenue streams, customize patient offerings, and use data to optimize operations. Dashboards are useful means to track such change. Healthcare organizations need to manage and protect sensitive information in a consistent, secure, and organized way.

Data Governance 52

Data Governance Measurement Modeling Metrics 52

Cloudera

OCTOBER 11, 2021

Modak Nabu relies on a framework of “Botworks”, a series of micro-jobs to accomplish various data transformation steps from ingestion to profiling, and indexing. Cloudera Data Engineering within CDP provides : Fully managed Spark-on-Kubernetes service that hides the complexity running production DE workloads at scale.

Data Lake 90

Data Lake Cost-Benefit Data-driven Dashboards 90