Cloudera

JANUARY 15, 2021

Cloud data warehouses allow users to run analytic workloads with greater agility, better isolation and scale, and lower administrative overhead than ever before. With pay-as-you-go pricing, platforms that deliver high-performance benefit users not only through faster results but also through direct cost savings.

Data Warehouse 96

Data Warehouse Cost-Benefit Consulting Interactive 96

Jet Global

SEPTEMBER 19, 2023

But the constant noise around the topic – from cost benefit analyses to sales pitches to technical overviews – has led to information overload. Data Access What insights can we derive from our cloud ERP? What are the best practices for analyzing cloud ERP data? How do I access the legacy data from my previous ERP?

Cost-Benefit 52

Cost-Benefit Data Warehouse Reporting Enterprise 52

AWS Big Data

JUNE 9, 2023

A modern data architecture enables companies to ingest virtually any type of data through automated pipelines into a data lake, which provides highly durable and cost-effective object storage at petabyte or exabyte scale.

Data Lake 113

Data Lake Metadata Optimization Statistics 113

Cloudera

JANUARY 11, 2021

At the same time, Central IT must juggle cost and risk. In data-driven organizations, to fulfill its charter to democratize data and provide on-demand, quality computing services in a secure, compliant environment, IT must replace legacy approaches and update technologies. We have this new data set, actually it is sensor data.

Data Warehouse 63

Data Warehouse Data Lake Cost-Benefit Machine Learning 63

AWS Big Data

AUGUST 1, 2023

Although Jira Cloud provides reporting capability, loading this data into a data lake will facilitate enrichment with other business data, as well as support the use of business intelligence (BI) tools and artificial intelligence (AI) and machine learning (ML) applications. Search for the Jira Cloud connector.

Data Lake 85

Data Lake Data Transformation Cost-Benefit Data-driven 85

AWS Big Data

NOVEMBER 8, 2023

Because Gilead is expanding into biologics and large molecule therapies, and has an ambitious goal of launching 10 innovative therapies by 2030, there is heavy emphasis on using data with AI and machine learning (ML) to accelerate the drug discovery pipeline. Loading data is a key process for any analytical system, including Amazon Redshift.

Data Lake 76

Data Lake Data Warehouse Cost-Benefit Optimization 76

DataKitchen

AUGUST 3, 2021

DataOps helps the data mesh deliver greater business agility by enabling decentralized domains to work in concert. . This post (1 of 5) is the beginning of a series that explores the benefits and challenges of implementing a data mesh and reviews lessons learned from a pharmaceutical industry data mesh example.

Data Architecture 246

Data Architecture Data Lake Cost-Benefit Data Warehouse 246

AWS Big Data

NOVEMBER 16, 2023

Amazon Redshift is a popular cloud data warehouse, offering a fully managed cloud-based service that seamlessly integrates with an organization’s Amazon Simple Storage Service (Amazon S3) data lake, real-time streams, machine learning (ML) workflows, transactional workflows, and much more—all while providing up to 7.9x

Enterprise 84

Enterprise Data Warehouse Snapshot Cost-Benefit 84

AWS Big Data

DECEMBER 21, 2023

The data volume is in double-digit TBs with steady growth as business and data sources evolve. smava’s Data Platform team faced the challenge to deliver data to stakeholders with different SLAs, while maintaining the flexibility to scale up and down while staying cost-efficient.

Data Lake 89

Data Lake Data Warehouse Data-driven B2B 89

AWS Big Data

MAY 16, 2024

To learn more details about their benefits, see Introduction to Spatial Indexes. Learn more about these differences in CARTO’s free ebook Spatial Indexes Benefits of H3 One of the flagship examples of spatial indexes is H3, which is a hexagonal spatial index. This ensures robust data representation in all directions.

Data Warehouse 108

Data Warehouse Visualization Cost-Benefit Optimization 108

Jet Global

MAY 9, 2024

The key components of a data pipeline are typically: Data Sources : The origin of the data, such as a relational database , data warehouse, data lake , file, API, or other data store. 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

AWS Big Data

NOVEMBER 16, 2023

Amazon Redshift is a popular cloud data warehouse, offering a fully managed cloud-based service that seamlessly integrates with an organization’s Amazon Simple Storage Service (Amazon S3) data lake, real-time streams, machine learning (ML) workflows, transactional workflows, and much more—all while providing up to 7.9x

Enterprise 85

Enterprise Data Warehouse Data Lake Optimization 85

IBM Big Data Hub

OCTOBER 16, 2023

It includes processes that trace and document the origin of data, models and associated metadata and pipelines for audits. Foundation models: The power of curated datasets Foundation models , also known as “transformers,” are modern, large-scale AI models trained on large amounts of raw, unlabeled data.

Risk 70

Risk Modeling Management Metadata 70

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. This is one of the biggest hurdles with the data vault approach. What is a dimensional data model?

Data Warehouse 65

Data Warehouse Data Lake Cost-Benefit Metadata 65

Sisense

JULY 8, 2020

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. In recent years we’ve seen data become vastly more available to businesses. This has allowed companies to become more and more data driven in all areas of their business.

Data Warehouse 90

Data Warehouse Data Lake Data-driven Cost-Benefit 90

DataKitchen

DECEMBER 7, 2021

This book is not available until January 2022, but considering all the hype around the data mesh, we expect it to be a best seller. In the book, author Zhamak Dehghani reveals that, despite the time, money, and effort poured into them, data warehouses and data lakes fail when applied at the scale and speed of today’s organizations.

Data-driven 246

Data-driven Data Governance Big Data Data Science 246

IBM Big Data Hub

APRIL 25, 2023

To do so, Presto and Spark need to readily work with existing and modern data warehouse infrastructures. Now, let’s chat about why data warehouse optimization is a key value of a data lakehouse strategy. The rise of cloud object storage has driven the cost of data storage down.

Optimization 56

Optimization Strategy Data Warehouse Cost-Benefit 56

AWS Big Data

MARCH 27, 2024

You can send data from your streaming source to this resource for ingesting the data into a Redshift data warehouse. This will be your online transaction processing (OLTP) data store for transactional data. With continuous innovations added to Amazon Redshift, it is now more than just a data warehouse.

Data Analytics 91

Data Analytics Analytics Data Warehouse Data Lake 91

Sisense

MAY 11, 2021

You can’t talk about data analytics without talking about data modeling. The reasons for this are simple: Before you can start analyzing data, huge datasets like data lakes must be modeled or transformed to be usable. Building the right data model is an important part of your data strategy.

Modeling 84

Modeling Big Data IoT Data Warehouse 84

DataKitchen

JULY 27, 2023

Azure Synapse Analytics Pipelines: Azure Synapse Analytics (formerly SQL Data Warehouse) provides data exploration, data preparation, data management, and data warehousing capabilities. It provides data prep, management, and enterprise data warehousing tools. It does the job.

Machine Learning 130

Machine Learning Cost-Benefit Data Transformation Testing 130

AWS Big Data

MARCH 25, 2024

Foundation models (FMs) are large machine learning (ML) models trained on a broad spectrum of unlabeled and generalized datasets. This scale and general-purpose adaptability are what makes FMs different from traditional ML models. FMs are multimodal; they work with different data types such as text, video, audio, and images.

Data Lake 90

Data Lake Unstructured Data Management Modeling 90

CIO Business Intelligence

APRIL 12, 2023

All of this needs to work cohesively in a real-time ecosystem and support the speed and scale necessary to realize the business benefits of real-time AI. Most current data architectures were designed for batch processing with analytics and machine learning models running on data warehouses and data lakes.

Machine Learning 131

Machine Learning Cost-Benefit Data-driven Strategy 131

Cloudera

OCTOBER 6, 2022

Gartner : “Digital transformation can refer to anything from IT modernization (for example, cloud computing), to digital optimization, to the invention of new digital business models.”. A major goal of these projects is cost reduction; it’s not sexy, it’s pragmatic. Cost savings opportunities. Strategies to maximize impact.

Digital Transformation 90

Digital Transformation Cost-Benefit Data Lake Machine Learning 90

AWS Big Data

MARCH 26, 2024

The following diagram illustrates the different pipelines to ingest data from various source systems using AWS services. Data storage Structured, semi-structured, or unstructured batch data is stored in an object storage because these are cost-efficient and durable.

Data Strategy 68

Data Strategy Strategy Data Warehouse Prescriptive Analytics 68

AWS Big Data

JANUARY 17, 2024

With Amazon EMR 6.15, we launched AWS Lake Formation based fine-grained access controls (FGAC) on Open Table Formats (OTFs), including Apache Hudi, Apache Iceberg, and Delta lake. Many large enterprise companies seek to use their transactional data lake to gain insights and improve decision-making.

Data Lake 93

Data Lake Snapshot Big Data Data-driven 93

AWS Big Data

NOVEMBER 8, 2023

High-quality data is not just about accuracy; it’s also about timeliness. To derive meaningful insights and ensure the optimal performance of machine learning (ML) and generative AI models, data needs to be ingested and processed in real time. With real-time streaming data, organizations can reimagine what’s possible.

Data-driven 89

Data-driven Data Lake Machine Learning Cost-Benefit 89

Cloudera

DECEMBER 12, 2018

After having rebuilt their data warehouse, I decided to take a little bit more of a pointed role, and I joined Oracle as a database performance engineer. I spent eight years in the real-world performance group where I specialized in high visibility and high impact data warehousing competes and benchmarks. you name it.

Data Warehouse 42

Data Warehouse Marketing Big Data Data Lake 42

Sisense

JULY 22, 2020

However, cloud computing has grown rapidly because it offers more flexible, agile, and cost-effective storage solutions. An effective, modern BI and analytics platform must be capable of working with all of these means of storing and generating data. Sisense provides instant access to your cloud data warehouses.

Slice and Dice 98

Slice and Dice Digital Transformation Data Warehouse Data Lake 98

AWS Big Data

MAY 7, 2024

Data governance is a key enabler for teams adopting a data-driven culture and operational model to drive innovation with data. Amazon DataZone allows you to simply and securely govern end-to-end data assets stored in your Amazon Redshift data warehouses or data lakes cataloged with the AWS Glue data catalog.

Metadata 75

Metadata Data Lake Data Processing Data-driven 75

BizAcuity

JULY 13, 2021

In many cases, source data is captured in various databases and the need for data consolidation arises and typically it takes around 6-9 months to complete, and with a high budget in terms of provisioning for servers, either in cloud or on-premise, licenses for data warehouse platform, reporting system, ETL tools, etc.

Optimization 52

Optimization Marketing Analytics Data Warehouse 52

Ontotext

FEBRUARY 12, 2024

This is especially beneficial when teams need to increase data product velocity with trust and data quality, reduce communication costs, and help data solutions align with business objectives. However, data mesh is not about introducing new technologies. by building data products with domain owners.

Data-driven 59

Data-driven Data Lake Data Quality Business Objectives 59

Ontotext

FEBRUARY 26, 2024

If one can figure out how to effectively reuse rockets, just like airplanes, the cost of access to space will be reduced by as much as a factor of a hundred.” ” Elon Musk SpaceX succeeded in building reusable rockets, drastically reducing the cost of sending them into orbit or taking astronauts to the International Space Station.

Technology 52

Technology Cost-Benefit Data-driven Metadata 52

Jet Global

JANUARY 15, 2021

These benefits come with a caveat, however. In this respect, we often hear references to “switching costs” and “stickiness.” When the cost of switching to a new product is high, customers tend to remain where they are. Ultimately, though, switching costs are not so much about absolute numbers as they are about relative costs.

Cost-Benefit 72

Cost-Benefit Data Lake Reporting OLAP 72

AWS Big Data

MARCH 27, 2024

Amazon Redshift is a fast, scalable, and fully managed cloud data warehouse that allows you to process and run your complex SQL analytics workloads on structured and semi-structured data. Cost Cloud services operate on a pay-as-you-go model, and estimating costs accurately can be challenging during a POC.

Testing 99

Testing Data Warehouse Metrics Cost-Benefit 99

IBM Big Data Hub

JANUARY 5, 2023

Ill-timed business decisions and misinformed business processes, missed revenue opportunities, failed business initiatives and complex data systems can all stem from data quality issues. Several factors determine the quality of your enterprise data like accuracy, completeness, consistency, to name a few.

Data Quality 52

Data Quality Data Architecture Strategy Data Lake 52

AWS Big Data

OCTOBER 4, 2023

Migrating on-premises data warehouses to the cloud is no longer viewed as an option but a necessity for companies to save cost and take advantage of what the latest technology has to offer. We also describe the main steps involved, the supported features, and their benefits.

Data Warehouse 59

Data Warehouse Cost-Benefit Metadata Data Lake 59

Domino Data Lab

JUNE 15, 2021

Over the next decade, the companies that will beat competitors will be “model-driven” businesses. These companies often undertake large data science efforts in order to shift from “data-driven” to “model-driven” operations, and to provide model-underpinned insights to the business. anomaly detection).

Modeling 69

Modeling Data Science Data-driven Data Warehouse 69