AWS Big Data

APRIL 3, 2024

They understand that a one-size-fits-all approach no longer works, and recognize the value in adopting scalable, flexible tools and open data formats to support interoperability in a modern data architecture to accelerate the delivery of new solutions.

Data Lake 98

Data Lake Snapshot Metadata Data Architecture 98

Cloudera

JUNE 18, 2022

These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. In recent years, the term “data lakehouse” was coined to describe this architectural pattern of tabular analytics over data in the data lake.

Data Lake 89

Data Lake Data Warehouse Machine Learning Cost-Benefit 89

IBM Big Data Hub

SEPTEMBER 19, 2023

Overview: Data science vs data analytics Think of data science as the overarching umbrella that covers a wide range of tasks performed to find patterns in large datasets, structure data for use, train machine learning models and develop artificial intelligence (AI) applications.

Data Science 82

Data Science Data Analytics Prescriptive Analytics Analytics 82

AWS Big Data

APRIL 29, 2024

The construction of big data applications based on open source software has become increasingly uncomplicated since the advent of projects like Data on EKS , an open source project from AWS to provide blueprints for building data and machine learning (ML) applications on Amazon Elastic Kubernetes Service (Amazon EKS).

Management 100

Management Big Data Metadata Data Warehouse 100

Cloudera

MARCH 17, 2023

As the use of ChatGPT becomes more prevalent, I frequently encounter customers and data users citing ChatGPT’s responses in their discussions. I love the enthusiasm surrounding ChatGPT and the eagerness to learn about modern data architectures such as data lakehouses, data meshes, and data fabrics.

Unstructured Data 60

Unstructured Data Data Lake Data Warehouse Machine Learning 60

CIO Business Intelligence

APRIL 25, 2022

The other 10% represents the effort of initial deployment, data-loading, configuration and the setup of administrative tasks and analysis that is specific to the customer, the Henschen said. Partner solutions to boost functionality, adoption.

Recreation/Entertainment 119

Recreation/Entertainment Data Lake Data Warehouse Unstructured Data 119

AWS Big Data

MAY 17, 2023

During that same time, AWS has been focused on helping customers manage their ever-growing volumes of data with tools like Amazon Redshift , the first fully managed, petabyte-scale cloud data warehouse. One group performed extract, transform, and load (ETL) operations to take raw data and make it available for analysis.

Data Warehouse 115

Data Warehouse Cost-Benefit Sales Data-driven 115

AWS Big Data

JANUARY 31, 2023

In this post, we are excited to summarize the features that the AWS Glue Data Catalog, AWS Glue crawler, and Lake Formation teams delivered in 2022. Whether you are a data platform builder, data engineer, data scientist, or any technology leader interested in data lake solutions, this post is for you.

Data Lake 84

Data Lake Data Governance Data Architecture Machine Learning 84

CIO Business Intelligence

JUNE 24, 2022

Your data architecture should also include the common data models of VSM tools to yield a holistic view,” Higgins said. Some of the other approaches include prioritizing cloud platforms to change technical architecture in a way to support business innovation, and embracing cloud-native to accelerate cloud modernization.

Modeling 105

Modeling Digital Transformation Data Architecture Data-driven 105

Cloudera

NOVEMBER 1, 2022

Through modern data architectures powered by CDP, including Cloudera-enabled data fabric, data lakehouse, and data mesh , DoD agencies can rapidly provision and manage innovative data engineering, data warehouse, and machine learning environments, with access to secured supply chain data stored in CDP Private Cloud.

Cost-Benefit 83

Cost-Benefit Data Architecture Risk IoT 83

CIO Business Intelligence

JUNE 23, 2023

Not only should the data strategy be cognizant of what’s in the IT and business strategies, it should also be embedded within those strategies as well, helping them unlock even more business value for the organization.

Data Strategy 116

Data Strategy Strategy Visualization Consulting 116

AWS Big Data

MARCH 10, 2023

However, as data processing at scale solutions grow, organizations need to build more and more features on top of their data lakes. Additionally, the task of maintaining and managing files in the data lake can be tedious and sometimes complex. Data can be organized into three different zones, as shown in the following figure.

Data Lake 107

Data Lake Sales Data Warehouse Snapshot 107

Cloudera

JANUARY 26, 2022

Modern, real-time businesses require accelerated cycles of innovation that are expensive and difficult to maintain with legacy data platforms. The hybrid cloud’s premise—two data architectures fused together—gives companies options to leverage those solutions and to address decision-making criteria, on a case-by-case basis. .

Data Processing 82

Data Processing IoT Cost-Benefit Digital Transformation 82

Cloudera

OCTOBER 11, 2022

This leads to the obvious question – how do you do data at scale ? Al needs machine learning (ML), ML needs data science. Data science needs analytics. And they all need lots of data. But it isn’t just aggregating data for models. Data needs to be prepared and analyzed.

Snapshot 89

Snapshot Data Science Digital Transformation Metadata 89

Alation

JULY 30, 2021

A part of that journey often involves moving fragmented on-premises data to a cloud data warehouse. You clearly shouldn’t move everything from your on-premises data warehouses. Otherwise, you can end up with a data swamp. Modern data catalogs leverage machine learning to locate potential high-value data.

Data Warehouse 52

Data Warehouse Data Governance Machine Learning Data-driven 52

CIO Business Intelligence

AUGUST 9, 2022

Database-centric: In larger organizations, where managing the flow of data is a full-time job, data engineers focus on analytics databases. Database-centric data engineers work with data warehouses across multiple databases and are responsible for developing table schemas. Data engineer job description.

Analytics 131

Analytics Data Science Statistics Unstructured Data 131

Data Virtualization

JANUARY 19, 2023

Reading Time: 2 minutes Today, many businesses are modernizing their on-premises data warehouses or cloud-based data lakes using Microsoft Azure Synapse Analytics. Unfortunately, with data spread.

Data Analytics 52

Data Analytics Data Lake Data Warehouse Analytics 52

AWS Big Data

MARCH 7, 2024

At the same time, they need to optimize operational costs to unlock the value of this data for timely insights and do so with a consistent performance. With this massive data growth, data proliferation across your data stores, data warehouse, and data lakes can become equally challenging.

Data Lake 117

Data Lake Analytics Dashboards Metrics 117

IBM Big Data Hub

JULY 5, 2022

In today’s world of complex data architectures and emerging technologies, databases can sometimes be undervalued and unrecognized. Nedbank builds a scalable data warehouse architecture . Endless data but your queries aren’t fast enough. Exxon transforms customer experiences .

Data Lake 93

Data Lake Data Warehouse Publishing Structured Data 93

AWS Big Data

APRIL 19, 2023

In this post, we look at three key challenges that customers face with growing data and how a modern data warehouse and analytics system like Amazon Redshift can meet these challenges across industries and segments. Nasdaq’s massive data growth meant they needed to evolve their data architecture to keep up.

Data Warehouse 56

Data Warehouse Data Lake Unstructured Data Optimization 56

Peter James Thomas

AUGUST 18, 2018

That was the Science, here comes the Technology… A Brief Hydrology of Data Lakes. Even back then, these were used for activities such as Analytics , Dashboards , Statistical Modelling , Data Mining and Advanced Visualisation. Of course some architectures featured both paradigms as well. In Closing.

Data Lake 63

Data Lake Data Warehouse Data mining Statistics 63

Jedox

OCTOBER 22, 2020

In addition to using data to inform your future decisions, you can also use current data to make immediate decisions. Some of the technologies that make modern data analytics so much more powerful than they used t be include data management, data mining, predictive analytics, machine learning and artificial intelligence.

Data Analytics 69

Data Analytics Analytics Unstructured Data Data mining 69

Cloudera

FEBRUARY 7, 2019

Enabling this transformation is the HDP platform, along with SAS Viya on Google Cloud , which has delivered machine learning models and personalization at scale. With the right technology now in place, ATB Financial is landing and curating more data than ever to bring data-driven insights to the business and its customers.

Big Data 63

Big Data Data Analytics Analytics Data Architecture 63

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. Both engines provide native ingestion support from Kinesis Data Streams and Amazon MSK via a separate streaming pipeline to a data lake or data warehouse for analysis.

Data Lake 94

Data Lake Unstructured Data Management Modeling 94

Cloudera

AUGUST 30, 2022

Modern data architectures. To eliminate or integrate these silos, the public sector needs to adopt robust data management solutions that support modern data architectures (MDAs). Towards Data Science ). Deploying modern data architectures. Forrester ).

Data Architecture 75

Data Architecture Data Lake Metadata Data Warehouse 75

AWS Big Data

FEBRUARY 8, 2023

Solution overview Vyaire’s iDataHub powered by AWS Glue has been effectively used for data movement between SAP ERP and ServiceMax. AWS Glue a serverless data integration service that makes it easy to discover, prepare, and combine data for analytics, machine learning (ML), and application development.

Testing 75

Testing Data Integration Data Lake Enterprise 75

Alation

APRIL 25, 2023

As firms mature their transformation efforts, applying Artificial Intelligence (AI), machine learning (ML) and Natural Language Processing (NLP) to the data is key to putting it into action quickly and effecitvely. Using bad data, or the incorrect data can generate devastating results. between 2022 and 2029.

Data Governance 52

Data Governance Marketing Machine Learning Sales 52

CIO Business Intelligence

SEPTEMBER 21, 2023

To make all this possible, the data had to be collected, processed, and fed into the systems that needed it in a reliable, efficient, scalable, and secure way. Data warehouses then evolved into data lakes, and then data fabrics and other enterprise-wide data architectures.

Enterprise 130

Enterprise Consulting Modeling Cost-Benefit 130

Alation

APRIL 25, 2023

As firms mature their transformation efforts, applying Artificial Intelligence (AI), machine learning (ML) and Natural Language Processing (NLP) to the data is key to putting it into action quickly and effecitvely. Using bad data, or the incorrect data can generate devastating results. between 2022 and 2029.

Data Governance 40

Data Governance Marketing Machine Learning Sales 40

AWS Big Data

NOVEMBER 29, 2023

In 2013, Amazon Web Services revolutionized the data warehousing industry by launching Amazon Redshift , the first fully-managed, petabyte-scale, enterprise-grade cloud data warehouse. Amazon Redshift made it simple and cost-effective to efficiently analyze large volumes of data using existing business intelligence tools.

Data Warehouse 104

Data Warehouse Data Lake Analytics Machine Learning 104

AWS Big Data

NOVEMBER 14, 2023

Amazon Redshift is a fast, fully managed cloud data warehouse that makes it straightforward and cost-effective to analyze all your data at petabyte scale, using standard SQL and your existing business intelligence (BI) tools. Today, tens of thousands of customers run business-critical workloads on Amazon Redshift.

Data Warehouse 60

Data Warehouse Analytics Testing Cost-Benefit 60

AWS Big Data

OCTOBER 18, 2023

Amazon Redshift is a fast, fully managed, petabyte-scale data warehouse that provides the flexibility to use provisioned or serverless compute for your analytical workloads. The decoupled compute and storage architecture of Amazon Redshift enables you to build highly scalable, resilient, and cost-effective workloads.

Analytics 99

Analytics Data Warehouse Testing Dashboards 99

BI-Survey

AUGUST 21, 2020

But what are the right measures to make the data warehouse and BI fit for the future? Can the basic nature of the data be proactively improved? The following insights came from a global BARC survey into the current status of data warehouse modernization. They are opting for cloud data services more frequently.

Data Warehouse 98

Data Warehouse Data Lake Data Governance Data Architecture 98

CIO Business Intelligence

NOVEMBER 25, 2022

Today, more than 90% of its applications run in the cloud, with most of its data is housed and analyzed in a homegrown enterprise data warehouse. Like many CIOs, Carhartt’s top digital leader is aware that data is the key to making advanced technologies work. Today, we backflush our data lake through our data warehouse.

Data Lake 128

Data Lake Data Warehouse Unstructured Data Data Architecture 128

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 95

Data Warehouse Data Lake Analytics Data Science 95

CIO Business Intelligence

APRIL 5, 2022

Investment in data warehouses is rapidly rising, projected to reach $51.18 billion by 2028 as the technology becomes a vital cog for enterprises seeking to be more data-driven by using advanced analytics. Data warehouses are, of course, no new concept. More data, more demanding. “As

Data Warehouse 98

Data Warehouse Visualization Data-driven Data Architecture 98

CIO Business Intelligence

NOVEMBER 29, 2022

A sea of complexity For years, data ecosystems have gotten more complex due to discrete (and not necessarily strategic) data-platform decisions aimed at addressing new projects, use cases, or initiatives. Layering technology on the overall data architecture introduces more complexity.

Data Architecture 111

Data Architecture Data Integration IoT Strategy 111