Sisense

OCTOBER 15, 2020

One of the main challenges when dealing with streaming data comes from performing stateful transformations for individual events. Unlike a batch processing job that runs within an isolated batch with clear start and end times, a stream processing job runs continuously on each event separately. Step 4: Query.

Dashboards 98

Dashboards IoT Optimization Internet of Things 98

AWS Big Data

MAY 16, 2023

Different communication infrastructure types such as mesh network and cellular can be used to send load information on a pre-defined schedule or event data in real time to the backend servers residing in the utility UDN (Utility Data Network).

Dashboards 92

Dashboards Statistics Data Collection Business Intelligence 92

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 98

Management Data Warehouse Digital Transformation Dashboards 98

O'Reilly on Data

JANUARY 17, 2023

If your business relied on a hard-and-fast rule, or a predictable sequence of events, someone was bound to write code to do the work and throw that on a few dozen servers to scale it out. That takes us to a conspicuous omission from that list of roles: the data scientists who focused on building basic models. And it made sense.

Machine Learning 363

Machine Learning Predictive Modeling Software Modeling 363

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

AWS Big Data

JANUARY 30, 2025

We used the AWS Step Function state machines to define, orchestrate, and execute our data pipelines. Amazon EventBridge We used Amazon EventBridge, the serverless event bus service, to define the event-based rules and schedules that would trigger our AWS Step Functions state machines.

Data Warehouse 52

Data Warehouse Data Architecture Machine Learning Data Transformation 52

FineReport

MARCH 7, 2024

As we explore examples of data analysis reports and interactive report data analysis dashboards, we embark on a journey to unravel the nuanced art of transforming raw data into meaningful narratives that empower decision-makers. Try FineReport Now 1. Try FineReport Now 1.1

Dashboards 52

Dashboards Reporting Advertising Statistics 52

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

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).

Metrics 87

Metrics Slice and Dice Data Warehouse Dashboards 87

AWS Big Data

OCTOBER 11, 2023

Due to this low complexity, the solution uses AWS serverless services to ingest the data, transform it, and make it available for analytics. The architecture uses AWS Lambda , a serverless, event-driven compute service that lets you run code without provisioning or managing servers. On the Datasets page, choose New data set.

Visualization 116

Visualization Dashboards Data-driven Gap analysis 116

AWS Big Data

JANUARY 6, 2025

Amazon AppFlow is a fully managed integration service that you can use to securely transfer data from software as a service (SaaS) applications, such as Google BigQuery, Salesforce, SAP, HubSpot, and ServiceNow, to Amazon Web Services (AWS) services such as Amazon Simple Storage Service (Amazon S3) and Amazon Redshift, in just a few clicks.

Analytics 97

Analytics Data Warehouse Metrics Big Data 97

AWS Big Data

NOVEMBER 9, 2023

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. It does this by helping teams handle the T in ETL (extract, transform, and load) processes.

Data Warehouse 123

Data Warehouse Testing Data Quality Reporting 123

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 96

Dashboards Visualization Metrics Data Transformation 96

AWS Big Data

SEPTEMBER 5, 2024

If storing operational data in a data warehouse is a requirement, synchronization of tables between operational data stores and Amazon Redshift tables is supported. In scenarios where data transformation is required, you can use Redshift stored procedures to modify data in Redshift tables.

IoT 110

IoT Data Warehouse Cost-Benefit Reporting 110

AWS Big Data

JANUARY 27, 2023

In this post, we show you how to use PCA’s data to build automated QuickSight dashboards for advanced analytics to assist in quality assurance (QA) and quality management (QM) processes. You can apply data, agent, call duration, and language filters for targeted search. Select -PCA-Dashboard and choose Share.

Analytics 71

Analytics Reporting Dashboards Visualization 71

AWS Big Data

NOVEMBER 13, 2023

The upstream data pipeline is a robust system that integrates various data sources, including Amazon Kinesis and Amazon Managed Streaming for Apache Kafka (Amazon MSK) for handling clickstream events, Amazon Relational Database Service (Amazon RDS) for delta transactions, and Amazon DynamoDB for delta game-related information.

Data Warehouse 109

Data Warehouse Analytics Data Lake Data Science 109

AWS Big Data

FEBRUARY 6, 2023

Amazon QuickSight dashboards showcase the results from the analyzer. Transform the YARN job history logs from JSON to CSV After obtaining YARN logs, you run a YARN log organizer, yarn-log-organizer.py, which is a parser to transform JSON-based logs to CSV files. The corresponding QuickSight dashboards include four charts.

Dashboards 90

Dashboards Optimization Data Lake Cost-Benefit 90

AWS Big Data

FEBRUARY 26, 2024

You simply configure your data sources to send information to OpenSearch Ingestion, which then automatically delivers the data to your specified destination. Additionally, you can configure OpenSearch Ingestion to apply data transformations before delivery. This allows for easy access and analysis of these events.

Dashboards 78

Dashboards Testing Metrics Optimization 78

Sisense

APRIL 10, 2020

In this article, we discuss how this data is accessed, an example environment and set-up to be used for data processing, sample lines of Python code to show the simplicity of data transformations using Pandas and how this simple architecture can enable you to unlock new insights from this data yourself.

Visualization 105

Visualization Reporting Data Processing Dashboards 105

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 83

Reporting Metrics Optimization Data Lake 83

IBM Big Data Hub

OCTOBER 16, 2023

Curated foundation models, such as those created by IBM or Microsoft, help enterprises scale and accelerate the use and impact of the most advanced AI capabilities using trusted data. In addition to natural language, models are trained on various modalities, such as code, time-series, tabular, geospatial and IT events data.

Risk 70

Risk Modeling Management Metadata 70

bridgei2i

SEPTEMBER 3, 2020

So first, the ability to capture and synthesize data signals from multiple and diverse sources as events occur. So you don’t have to wait for a month to get data. You can, again, wait for two weeks after an event has happened. You need to know that the event is happening and do something about it now.

Enterprise 94

Enterprise Insurance Digital Transformation Interactive 94

AWS Big Data

MARCH 3, 2023

Additionally, the scale is significant because the multi-tenant data sources provide a continuous stream of testing activity, and our users require quick data refreshes as well as historical context for up to a decade due to compliance and regulatory demands. Finally, data integrity is of paramount importance.

Software 52

Software Data Lake Testing Cost-Benefit 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

Sisense

MAY 11, 2021

When it comes to data modeling, function determines form. Let’s say you want to subject a dataset to some form of anomaly detection; your model might take the form of a singular event stream that can be read by an anomaly detection service.

Modeling 84

Modeling Big Data IoT Data Warehouse 84

AWS Big Data

JUNE 29, 2023

Kinesis Data Analytics for Apache Flink In our example, we perform the following actions on the streaming data: Connect to an Amazon Kinesis Data Streams data stream. View the stream data. Transform and enrich the data. Manipulate the data with Python. Open the file to inspect the new data.

Data Analytics 91

Data Analytics Analytics IoT Data Lake 91

Alation

OCTOBER 28, 2021

These mandates ensure that PHA and PII data are protected and managed properly, so that patients are protected in the event of data breaches. Yet this same data is critical to improving patient outcomes. Dashboards are useful means to track such change.

Data Governance 52

Data Governance Measurement Data Quality Metrics 52

AWS Big Data

SEPTEMBER 19, 2023

Problem statement In order to keep up with the rapid movement of fraudsters, our decision platform must continuously monitor user events and respond in real-time. However, our legacy data warehouse-based solution was not equipped for this challenge. Amazon DynamoDB is another data source for our Streaming 2.0

Analytics 98

Analytics Risk Big Data Machine Learning 98

Jet Global

MAY 28, 2019

A database is, by definition, ‘any collection of data organized for storage, accessibility, and retrieval.’ Databases usually consist of information arranged in rows, columns, and tables, organized mainly for easy input and collection of different events. while rows will contain the individual events and trades themselves.

Data Warehouse 85

Data Warehouse Reporting Business Intelligence Sales 85

AWS Big Data

MARCH 15, 2023

Performance and scalability of both the data pipeline and API endpoint were key success criteria. The data pipeline needed to have sufficient performance to allow for fast turnaround in the event that data issues needed to be corrected.

Cost-Benefit 79

Cost-Benefit Data Processing Optimization Data-driven 79

CIO Business Intelligence

AUGUST 7, 2024

The project’s primary objectives were to maintain 100% functionality of the EMR during planned failover events; achieving a recovery point objective of less than one minute; and meet a recovery time objective of two hours for critical services. It also crafted multiple machine learning and AI models to tackle business challenges.

IT 119

IT Insurance Cost-Benefit Testing 119

Birst BI

FEBRUARY 25, 2020

Register for March 19 Birst and Snowflake online event featuring the fifth-largest consumer bank in the United States. The benefits of Birst’s cloud-native analytics platform powered by Snowflake’s world-class cloud data warehouse are numerous, especially as cloud becomes the first choice for enterprise data transformation initiatives.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Architecture Enterprise 52

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

Jet Global

MAY 9, 2024

Data Extraction : The process of gathering data from disparate sources, each of which may have its own schema defining the structure and format of the data and making it available for processing. This can include tasks such as data ingestion, cleansing, filtering, aggregation, or standardization.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 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 Visualization 52

Jet Global

JULY 16, 2024

Imagine trying to analyze data with a constantly changing backend—it’s like kicking the legs out from underneath a table and still expecting it to stay upright. Your dashboards and reports need a stable foundation for your data to work correctly! What is Apache Iceberg?

Dashboards 52

Dashboards Data-driven Reporting Business Intelligence 52

Jet Global

OCTOBER 1, 2024

Trino allows users to run ad hoc queries across massive datasets, making real-time decision-making a reality without needing extensive data transformations. This is particularly valuable for teams that require instant answers from their data. Data Lake Analytics: Trino doesn’t just stop at databases.

Dashboards 52

Dashboards Data Lake Reporting Cost-Benefit 52