AWS Big Data

MAY 18, 2023

It’s even harder when your organization is dealing with silos that impede data access across different data stores. Seamless data integration is a key requirement in a modern data architecture to break down data silos. He is passionate about distributed computing and everything and anything about the data.

Testing 75

Testing Data Lake Cost-Benefit Data Integration 75

AWS Big Data

MARCH 27, 2024

AWS has invested in a zero-ETL (extract, transform, and load) future so that builders can focus more on creating value from data, instead of having to spend time preparing data for analysis. You can send data from your streaming source to this resource for ingesting the data into a Redshift data warehouse.

Data Analytics 90

Data Analytics Analytics Data Warehouse Data Lake 90

Andrew White

OCTOBER 22, 2021

Lakehouse (data warehouse and data lake working together) 8. Data Literacy, training, coordination, collaboration 8. Data Management Infrastructure/Data Fabric 5. Data Integration tactics 4. Figure 3: The Data and Analytics (infrastructure) Continuum. Metadata Strategy 3.

IT 52

IT Data Lake Strategy Data Science 52

Data Virtualization

FEBRUARY 17, 2022

The post What is Data Virtualization? Understanding the Concept and its Advantages appeared first on Data Virtualization blog - Data Integration and Modern Data Management Articles, Analysis and Information. However, every day, companies generate.

IT 82

IT Data Integration Management Data Lake 82

IBM Big Data Hub

DECEMBER 16, 2022

For example, data catalogs have evolved to deliver governance capabilities like managing data quality and data privacy and compliance. It uses metadata and data management tools to organize all data assets within your organization. She also wants to predict future sales of both shoes and jewelry.

Metadata 52

Metadata Data Quality Data-driven Data Governance 52

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

MAY 30, 2023

Customers have been using data warehousing solutions to perform their traditional analytics tasks. Traditional batch ingestion and processing pipelines that involve operations such as data cleaning and joining with reference data are straightforward to create and cost-efficient to maintain. options(**additional_options).mode("append").save(s3_output_folder)

Data Lake 77

Data Lake Data Analytics Analytics Data Processing 77

AWS Big Data

FEBRUARY 22, 2023

In this post, we show how Ruparupa implemented an incrementally updated data lake to get insights into their business using Amazon Simple Storage Service (Amazon S3), AWS Glue , Apache Hudi , and Amazon QuickSight. An AWS Glue ETL job, using the Apache Hudi connector, updates the S3 data lake hourly with incremental data.

Data Lake 52

Data Lake Dashboards Cost-Benefit Metadata 52

AWS Big Data

FEBRUARY 21, 2023

Data warehouses play a vital role in healthcare decision-making and serve as a repository of historical data. A healthcare data warehouse can be a single source of truth for clinical quality control systems. What is a dimensional data model? What is a dimensional data model?

Data Warehouse 63

Data Warehouse Data Lake Cost-Benefit Modeling 63

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

DataKitchen

JULY 27, 2023

Let’s go through the ten Azure data pipeline tools Azure Data Factory : This cloud-based data integration service allows you to create data-driven workflows for orchestrating and automating data movement and transformation. You can use it for big data analytics and machine learning workloads.

Machine Learning 130

Machine Learning Cost-Benefit Data Transformation Testing 130

CIO Business Intelligence

MAY 24, 2022

Organisations have to contend with legacy data and increasing volumes of data spread across multiple silos. To meet these demands many IT teams find themselves being systems integrators, having to find ways to access and manipulate large volumes of data for multiple business functions and use cases. zettabytes of data.

Data-driven 80

Data-driven Data Lake Data Warehouse Cost-Benefit 80

AWS Big Data

MARCH 26, 2024

Data ingestion You have to build ingestion pipelines based on factors like types of data sources (on-premises data stores, files, SaaS applications, third-party data), and flow of data (unbounded streams or batch data). Data exploration Data exploration helps unearth inconsistencies, outliers, or errors.

Data Strategy 69

Data Strategy Strategy Data Warehouse Prescriptive Analytics 69

AWS Big Data

JULY 12, 2023

Introduction to Amazon Redshift Amazon Redshift is a fast, fully-managed, self-learning, self-tuning, petabyte-scale, ANSI-SQL compatible, and secure cloud data warehouse. Thousands of customers use Amazon Redshift to analyze exabytes of data and run complex analytical queries.

Data Warehouse 52

Data Warehouse Modeling Dashboards Data Lake 52

IBM Big Data Hub

APRIL 27, 2022

The data fabric architectural approach can simplify data access in an organization and facilitate self-service data consumption at scale. Read: The first capability of a data fabric is a semantic knowledge data catalog, but what are the other 5 core capabilities of a data fabric? 11 May 2021. .

Management 87

Management Metadata Data Architecture Data Lake 87

CIO Business Intelligence

MARCH 22, 2022

Which type(s) of storage consolidation you use depends on the data you generate and collect. . One option is a data lake—on-premises or in the cloud—that stores unprocessed data in any type of format, structured or unstructured, and can be queried in aggregate. Set up unified data governance rules and processes.

Analytics 96

Analytics Key Performance Indicator Data Warehouse Data-driven 96

AWS Big Data

JULY 13, 2023

Generating business outcomes In 4 days, the Altron SI team left the Immersion Day workshop with the following: A data pipeline ingesting data from 21 sources (SQL tables and files) and combining them into three mastered and harmonized views that are cataloged for Altron’s B2B accounts.

Optimization 88

Optimization B2B Data Quality Sales 88

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

BizAcuity

AUGUST 1, 2022

TIBCO Jaspersoft offers a complete BI suite that includes reporting, online analytical processing (OLAP), visual analytics , and data integration. The web-scale platform enables users to share interactive dashboards and data from a single page with individuals across the enterprise.

Reporting 52

Reporting OLAP Online Analytical Processing Dashboards 52

Data Virtualization

JANUARY 30, 2019

In this article, I will discuss the complexity of data migration when transitioning to a new system, based on the traditional ways of working. I will explain why data virtualization can play a role in taking away this complexity, for. The post How Much Time Could Your Company Save If You Said Goodbye to Data Migration?

Management 40

Management Data Lake Data Warehouse Data Integration 40

IBM Big Data Hub

OCTOBER 12, 2023

Stored data is predicted to see a 250% growth by 2025, 1 the results of which are likely to include a greater number of disconnected silos and higher associated costs. To optimize data analytics and AI workloads, organizations need a data store built on an open data lakehouse architecture.

Cost-Benefit 83

Cost-Benefit Metadata Data Governance Modeling 83

Ontotext

FEBRUARY 26, 2024

Firstly, on the data maturity spectrum, the vast majority of organizations I’ve spoken with are stuck in the information stage. They have massive amounts of data they’re collecting and storing in their relational databases, document stores, data lakes, and data warehouses.

Technology 52

Technology Cost-Benefit Data-driven Metadata 52

AWS Big Data

DECEMBER 18, 2023

Amazon Redshift powers data-driven decisions for tens of thousands of customers every day with a fully managed, AI-powered cloud data warehouse, delivering the best price-performance for your analytics workloads. Discover how you can use Amazon Redshift to build a data mesh architecture to analyze your data.

Data Warehouse 98

Data Warehouse Machine Learning Data-driven Data Lake 98

Data Virtualization

APRIL 14, 2021

If you are in the data management world, you probably help your company to redefine its data analytics architecture, especially in the context of cloud adoption. At some point in the process, someone might have stared at the myriad boxes.

Data Analytics 52

Data Analytics Management Analytics Data Warehouse 52

IBM Big Data Hub

AUGUST 4, 2023

By leveraging data services and APIs, a data fabric can also pull together data from legacy systems, data lakes, data warehouses and SQL databases, providing a holistic view into business performance. Then, it applies these insights to automate and orchestrate the data lifecycle.

Data Architecture 64

Data Architecture Data Lake Machine Learning Data Governance 64

Alation

JANUARY 27, 2022

How do businesses transform raw data into competitive insights? Data analytics. Modern businesses are increasingly leveraging analytics for a range of use cases. Analytics can help a business improve customer relationships, optimize advertising campaigns, develop new products, and much more. What is Data Analytics?

Data Governance 52

Data Governance Analytics Cost-Benefit Data-driven 52

Jet Global

MAY 9, 2024

A data pipeline is a series of processes that move raw data from one or more sources to one or more destinations, often transforming and processing the data along the way. Data pipelines support data science and business intelligence projects by providing data engineers with high-quality, consistent, and easily accessible data.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52

Jet Global

JUNE 13, 2022

When migrating to the cloud, there are a variety of different approaches you can take to maintain your data strategy. Those options include: Data lake or Azure Data Lake Services (ADLS) is Microsoft’s new data solution, which provides unstructured date analytics through AI.

Reporting 52

Reporting Data Lake Sales Operational Reporting 52

Jet Global

APRIL 26, 2022

Jet Reports now offers high performance connectivity with options to connect to Synapse/Azure Data Lakes, BYOD, SQL or your Cubes and Tabular models. So D365 F&SCM customers can enjoy all the reporting benefits that the GP, NAV, and BC community already have. With the release of Jet Reports 22.1,

Reporting 52

Reporting Finance Cost-Benefit Forecasting 52

Jet Global

SEPTEMBER 30, 2022

What are the best practices for analyzing cloud ERP data? How can we respond in real time to the company’s analytic needs? Data Management. How do we create a data warehouse or data lake in the cloud using our cloud ERP? How do I access the legacy data from my previous ERP? Self-service BI.

Reporting 52

Reporting Data Warehouse Operational Reporting Enterprise 52