AWS Big Data

NOVEMBER 13, 2023

Amazon Redshift is a fully managed data warehousing service that offers both provisioned and serverless options, making it more efficient to run and scale analytics without having to manage your data warehouse. These upstream data sources constitute the data producer components.

Data Warehouse 90

Data Warehouse Data Lake Analytics Data Science 90

AWS Big Data

JANUARY 17, 2024

His expertise lies in assisting customers with migrating intricate enterprise systems and databases to AWS, constructing enterprise data warehousing and data lake platforms. He is deeply passionate about applying ML/DL and big data techniques to solve real-world problems. Aditya Shah is a Software Development Engineer at AWS.

Data Lake 91

Data Lake Snapshot Big Data Data-driven 91

CIO Business Intelligence

JUNE 29, 2022

The recent announcement of the Microsoft Intelligent Data Platform makes that more obvious, though analytics is only one part of that new brand. Azure Data Factory. Azure Data Lake Analytics. Data warehouses are designed for questions you already know you want to ask about your data, again and again.

Data Lake 116

Data Lake Analytics Data Warehouse Machine Learning 116

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. Satesh Sonti is a Sr.

Data Warehouse 94

Data Warehouse Insurance Statistics Software 94

Cloudera

JUNE 17, 2022

In the second blog of the Universal Data Distribution blog series , we explored how Cloudera DataFlow for the Public Cloud (CDF-PC) can help you implement use cases like data lakehouse and data warehouse ingest, cybersecurity, and log optimization, as well as IoT and streaming data collection.

Cost-Benefit 88

Cost-Benefit IoT Data Warehouse Manufacturing 88

CIO Business Intelligence

DECEMBER 22, 2022

DataOps in practice To make the most of DataOps, enterprises must evolve their data management strategies to deal with data at scale and in response to real-world events as they happen, according to Dunning and Friedman. They also note DataOps fits well with microservices architectures.

Analytics 130

Analytics Machine Learning Software Data Quality 130

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

AWS Big Data

APRIL 27, 2023

With these features, you can now build data pipelines completely in standard SQL that are serverless, more simple to build, and able to operate at scale. Typically, data transformation processes are used to perform this operation, and a final consistent view is stored in an S3 bucket or folder.

Data Lake 72

Data Lake Snapshot Optimization Data Transformation 72

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

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. This design philosophy was adapted from our friends at Fishtown Analytics.).

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.

Data Analytics 72

Data Analytics Analytics IoT Data Lake 72

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 84

Data Warehouse Machine Learning Data Integration Data-driven 84

Smart Data Collective

OCTOBER 13, 2021

There are countless examples of big data transforming many different industries. There is no disputing the fact that the collection and analysis of massive amounts of unstructured data has been a huge breakthrough. How does Data Virtualization complement Data Warehousing and SOA Architectures?

Visualization 135

Visualization Cost-Benefit Big Data Prescriptive Analytics 135

Rocket-Powered Data Science

MARCH 20, 2023

In fact, by putting a single label like AI on all the steps of a data-driven business process, we have effectively not only blurred the process, but we have also blurred the particular characteristics that make each step separately distinct, uniquely critical, and ultimately dependent on specialized, specific technologies at each step.

Data Warehouse 324

Data Warehouse Metadata Digital Transformation Unstructured Data 324

Jet Global

MAY 28, 2019

Whether the reporting is being done by an end user, a data science team, or an AI algorithm, the future of your business depends on your ability to use data to drive better quality for your customers at a lower cost. So, when it comes to collecting, storing, and analyzing data, what is the right choice for your enterprise?

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 65

Cost-Benefit Data Processing Optimization Data-driven 65

Birst BI

FEBRUARY 25, 2020

Managing large-scale data warehouse systems has been known to be very administrative, costly, and lead to analytic silos. The good news is that Snowflake, the cloud data platform, lowers costs and administrative overhead. When did you begin a technology partnership with Snowflake and why?

Data Warehouse 52

Data Warehouse Cost-Benefit Data Architecture Enterprise 52

AWS Big Data

AUGUST 1, 2023

You can do this by updating the CloudFormation stack with a flag that includes the CDC and data transformation steps. This will enable both the CDC steps and the data transformation steps for the Jira data. The DataBrew job performs data transformation and filtering tasks. Choose Update.

Data Lake 83

Data Lake Data Transformation Cost-Benefit Data-driven 83

AWS Big Data

DECEMBER 21, 2023

To speed up the self-service analytics and foster innovation based on data, a solution was needed to provide ways to allow any team to create data products on their own in a decentralized manner. To create and manage the data products, smava uses Amazon Redshift , a cloud data warehouse.

Data Lake 87

Data Lake Data Warehouse B2B Data-driven 87

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 77

Analytics Risk Big Data Machine Learning 77

Jet Global

APRIL 24, 2024

This approach allows you and your customers to harness the full potential of your data, transforming it into interactive, AI-driven conversations that can significantly enhance user engagement and insight discovery. Unlike competitors who lock you into their pre-built AI solutions, Logi AI empowers you with the freedom to choose.

Business Intelligence 52

Business Intelligence Dashboards Software Reporting 52

Jet Global

AUGUST 24, 2023

It streamlines data integration, ensures real-time access to accurate information, enhances collaboration, and provides the flexibility needed to adapt to evolving ERP systems and business requirements. Data transformation ensures that the data aligns with the requirements of the new cloud ERP system. Privacy Policy.

Finance 52

Finance Reporting Data Integration Risk 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

Jet Global

OCTOBER 30, 2023

Together, CXO and Power BI provide you with access to insights from both EPM and BI data in one tool. You can now elevate their decision-making process by drilling down into more detailed data, and enriching EPM figures with non-financial data. Transforming Financial Reporting with Dynamic Dashboards Download Now 1.

Dashboards 52

Dashboards Reporting Operational Reporting Software 52

Jet Global

JULY 19, 2023

Data Connectivity Enhancements Data and content authors are the first users in the app building infrastructure and content. It is important for our customers to access advanced connectors and data transformation features so they can build a robust data layer. I understand that I can withdraw my consent at any time.

Dashboards 52

Dashboards Visualization Reporting Interactive 52

Jet Global

NOVEMBER 7, 2023

The answer depends on your specific business needs and the nature of the data you are working with. Both methods have advantages and disadvantages: Replication involves periodically copying data from a source system to a data warehouse or reporting database. Empower your team to add new data sources on the fly.

Enterprise 52

Enterprise Data Warehouse Operational Reporting Reporting 52

Jet Global

AUGUST 9, 2023

Speed time to market with faster data migration, easier data transformation. Wands for SAP Wands for SAP empowers your finance team to leverage their existing Excel skills to streamline data entry to drive efficiencies in your month-end process. Time-to-value acceleration — Quick installation. Privacy Policy.

Finance 52

Finance Reporting Management Enterprise 52

Jet Global

MARCH 14, 2024

Data Lineage and Documentation Jet Analytics simplifies the process of documenting data assets and tracking data lineage in Fabric. It offers a transparent and accurate view of how data flows through the system, ensuring robust compliance. I understand that I can withdraw my consent at any time. Privacy Policy.

Analytics 52

Analytics Management Reporting Enterprise 52

Jet Global

MARCH 13, 2024

Complex Data Structures and Integration Processes Dynamics data structures are already complex – finance teams navigating Dynamics data frequently require IT department support to complete their routine reporting. I understand that I can withdraw my consent at any time. Privacy Policy.

Reporting 52

Reporting Finance Data Quality Sales 52

Jet Global

MAY 1, 2023

These sit on top of data warehouses that are strictly governed by IT departments. The role of traditional BI platforms is to collect data from various business systems. Strategic Objective Create a complete, user-friendly view of the data by preparing it for analysis. addresses). Privacy Policy.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52