AWS Big Data

DECEMBER 21, 2023

To create and manage the data products, smava uses Amazon Redshift , a cloud data warehouse. In this post, we show how smava optimized their data platform by using Amazon Redshift Serverless and Amazon Redshift data sharing to overcome right-sizing challenges for unpredictable workloads and further improve price-performance.

Data Lake 91

Data Lake Data Warehouse Data-driven B2B 91

Cloudera

NOVEMBER 25, 2020

How can users quickly pull up historical trails, what results were generated, what steps were involved, and compare against external text data? Innovate on serviceability and optimize utilization. The Vision of a Discovery Data Warehouse. A Discovery Data Warehouse is cloud-agnostic.

Data Warehouse 58

Data Warehouse Unstructured Data Analytics Visualization 58

AWS Big Data

APRIL 4, 2024

Amazon Redshift is a recommended service for online analytical processing (OLAP) workloads such as cloud data warehouses, data marts, and other analytical data stores. Data sharing provides live access to data so that you always see the most up-to-date and consistent information as it’s updated in the data warehouse.

Big Data 68

Big Data Data Warehouse Advertising OLAP 68

CIO Business Intelligence

MARCH 9, 2022

But the data repository options that have been around for a while tend to fall short in their ability to serve as the foundation for big data analytics powered by AI. Traditional data warehouses, for example, support datasets from multiple sources but require a consistent data structure.

Data Lake 95

Data Lake Unstructured Data Data Warehouse Data Quality 95

CIO Business Intelligence

NOVEMBER 14, 2022

A DSS leverages a combination of raw data, documents, personal knowledge, and/or business models to help users make decisions. The data sources used by a DSS could include relational data sources, cubes, data warehouses, electronic health records (EHRs), revenue projections, sales projections, and more.

Data mining 123

Data mining Data-driven Statistics OLAP 123

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

CIO Business Intelligence

AUGUST 18, 2022

Traditionally, organizations have maintained two systems as part of their data strategies: a system of record on which to run their business and a system of insight such as a data warehouse from which to gather business intelligence (BI). You can intuitively query the data from the data lake.

Data Lake 139

Data Lake Data Warehouse Unstructured Data Business Intelligence 139

Cloudera

APRIL 1, 2024

The following are key attributes of our platform that set Cloudera apart: Unlock the Value of Data While Accelerating Analytics and AI The data lakehouse revolutionizes the ability to unlock the power of data. At Cloudera, we are embedding AI in all our products to improve productivity of data professionals.

Unstructured Data 104

Unstructured Data Cost-Benefit Metadata Machine Learning 104

CIO Business Intelligence

APRIL 25, 2022

The data lakehouse is a relatively new data architecture concept, first championed by Cloudera, which offers both storage and analytics capabilities as part of the same solution, in contrast to the concepts for data lake and data warehouse which, respectively, store data in native format, and structured data, often in SQL format.

Recreation/Entertainment 103

Recreation/Entertainment Data Lake Data Warehouse Unstructured Data 103

Sisense

APRIL 26, 2020

Read on to explore more about structured vs unstructured data, why the difference between structured and unstructured data matters, and how cloud data warehouses deal with them both. Structured vs unstructured data. However, both types of data play an important role in data analysis.

Unstructured Data 52

Unstructured Data Data Warehouse Structured Data Data mining 52

AWS Big Data

FEBRUARY 20, 2024

Managed AWS Analytics and Database services allow for each component of the solution, from ingestion to analysis, to be optimized for speed, with little management overhead. DynamoDB is a managed NoSQL database solution that acts as a key-value store for transactional data.

Visualization 101

Visualization Cost-Benefit Optimization B2B 101

Octopai

MARCH 22, 2023

Data migration can be a daunting task, especially when dealing with large volumes of data. Snowflake is one of the leading cloud-based data warehouse that provides scalability, flexibility, and ease of use. Snowflake data warehouse platform has been designed to leverage the power of modern-day cloud computing technology.

Cost-Benefit 78

Cost-Benefit Data Warehouse Unstructured Data Optimization 78

Cloudera

SEPTEMBER 17, 2020

To address this, they focused on creating an experimentation-oriented culture, enabled thanks to a cloud-native platform supporting the full data lifecycle. This platform, including an ad-hoc capable data warehouse service with built-in, easy-to-use visualization, made it easy for anyone to jump in and start experimenting.

Experimentation 81

Experimentation Data Warehouse Dashboards Visualization 81

CDW Research Hub

APRIL 20, 2020

Many organizations move from a traditional data warehouse to a hybrid or cloud-based data warehouse to help alleviate their struggles with rapidly expanding data, new users and use cases, and a growing number of diverse tools and applications. Connecting ThoughtSpot and Snowflake is a simple 3-step process.

Data Warehouse 52

Data Warehouse Consulting Data-driven Structured Data 52

CIO Business Intelligence

FEBRUARY 16, 2023

Hence the drive to provide ML as a service to the Data & Tech team’s internal customers. All they would have to do is just build their model and run with it,” he says. That step, primarily undertaken by developers and data architects, established data governance and data integration. The offensive side?

Unstructured Data 98

Unstructured Data Data Lake Prescriptive Analytics Digital Transformation 98

AWS Big Data

MARCH 26, 2024

Unified customer profile Graph databases excel in modeling customer interactions and relationships, offering a comprehensive view of the customer journey. The AWS modern data architecture shows a way to build a purpose-built, secure, and scalable data platform in the cloud.

Data Strategy 69

Data Strategy Strategy Data Warehouse Prescriptive Analytics 69

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. Complete the implementation tasks such as data ingestion and performance testing.

Testing 100

Testing Data Warehouse Metrics Cost-Benefit 100

Alation

MAY 16, 2023

What is a Data Pipeline? A data pipeline is a series of processing steps that move data from its source to its destination. The various steps along the pipeline involve transforming, optimizing, cleaning, filtering, integrating, and aggregating the data. The end result is data that is ready to be analyzed.

Data Lake 69

Data Lake Data Governance Data Warehouse Data Processing 69

AWS Big Data

MARCH 7, 2023

Flexible and easy to use – The solutions should provide less restrictive, easy-to-access, and ready-to-use data. They should also provide optimal performance with low or no tuning. Data lakes are more focused around storing and maintaining all the data in an organization in one place.

Analytics 73

Analytics Data Warehouse Data Lake Metadata 73

Jet Global

SEPTEMBER 4, 2020

Consultants and developers familiar with the AX data model could query the database using any number of different tools, including a myriad of different report writers. Data entities are more secure and arguably easier to master than the relational database model, but one downside is there are lots of them!

Data Lake 88

Data Lake OLAP Data Warehouse Unstructured Data 88

IBM Big Data Hub

JANUARY 18, 2023

A read-optimized platform that can integrate data from multiple applications emerged. In another decade, the internet and mobile started the generate data of unforeseen volume, variety and velocity. It required a different data platform solution. This adds an additional ETL step, making the data even more stale.

Data Lake 52

Data Lake Data Warehouse Data-driven Metadata 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

Sisense

JUNE 8, 2020

Datasets are on the rise and most of that data is on the cloud. The recent rise of cloud data warehouses like Snowflake means businesses can better leverage all their data using Sisense seamlessly with products like the Snowflake Cloud Data Platform to strengthen their businesses.

Data Warehouse 89

Data Warehouse Data-driven Dashboards Sales 89

CIO Business Intelligence

MAY 10, 2022

A customer data platform (CDP) is a prepackaged, unified customer database that pulls data from multiple sources to create customer profiles of structured data available to other marketing systems. Bringing all that data together helps you deliver personalized experiences to each customer. Treasure Data CDP.

Advertising 98

Advertising Interactive Marketing Data Integration 98

FineReport

JUNE 24, 2021

Business intelligence can assist decision-making and operation optimization, either at the operational or tactical, or strategic levels. Technicals such as data warehouse, online analytical processing (OLAP) tools, and data mining are often binding. Data preparation and data processing.

Business Intelligence 84

Business Intelligence OLAP Data mining Visualization 84

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 91

Data Lake Unstructured Data Management Modeling 91

Alation

MAY 16, 2023

What is a Data Pipeline? A data pipeline is a series of processing steps that move data from its source to its destination. The various steps along the pipeline involve transforming, optimizing, cleaning, filtering, integrating, and aggregating the data. The end result is data that is ready to be analyzed.

Data Lake 40

Data Lake Data Governance Data Warehouse Data Processing 40

IBM Big Data Hub

JULY 5, 2022

Nedbank builds a scalable data warehouse architecture . Endless data but your queries aren’t fast enough. Empower real-time decision making and perform heavy computational analysis with built-in ML, insanely fast ingest, and querying of data in motion and at rest. Exxon transforms customer experiences .

Data Lake 88

Data Lake Data Warehouse Publishing Structured Data 88

Sisense

MARCH 14, 2021

Looking at the diagram, we see that Business Intelligence (BI) is a collection of analytical methods applied to big data to surface actionable intelligence by identifying patterns in voluminous data. As we move from right to left in the diagram, from big data to BI, we notice that unstructured data transforms into structured data.

Big Data 52

Big Data IoT Data Warehouse Data-driven 52

Sisense

JUNE 30, 2020

In this diagram , visual analytics is shown to be the foundation for interactive data, thereby demonstrating how the two are connected. Analytics acts as the source for data visualization and contributes to the health of any organization by identifying underlying models and patterns and predicting needs.

Visualization 93

Visualization Analytics Dashboards Data-driven 93

Cloudera

OCTOBER 17, 2023

Streaming data absolutely has a tremendous role to play in generative AI, in fine tuning foundational models, optimizing prompts, contextualizing and augmenting outputs, etc. Cloudera perspective: Data streams are part of a much broader data lifecycle. Stay tuned for plenty more on that topic!

Data-driven 77

Data-driven Enterprise IoT Data Warehouse 77

AWS Big Data

JUNE 6, 2023

In this post we showcase how we used AWS Glue to move siloed digital analytics data, with inconsistent arrival times, to AWS S3 (our Data Lake) and our central data warehouse (DWH), Snowflake. AWS Glue gave us a cost-efficient option to migrate the data and we further optimized storage cost by pruning cold data.

Analytics 55

Analytics Data Lake Testing Optimization 55

Ontotext

MARCH 8, 2023

Specifically, the increasing amount of data being generated and collected, and the need to make sense of it, and its use in artificial intelligence and machine learning, which can benefit from the structured data and context provided by knowledge graphs. We get this question regularly. million users.

Enterprise 52

Enterprise Knowledge Discovery Risk Data-driven 52

CDW Research Hub

APRIL 28, 2020

Snowflake has been optimized for speed and performance by separating compute and storage. This gives you the flexibility to scale your cloud data platform to meet peak loads, and then scale back down for fast and affordable data queries. A pay-as-you-go billing model to eliminate lengthy procurement processes.

Data-driven 52

Data-driven Analytics Consulting ROI 52

Sisense

OCTOBER 6, 2020

And, as industrial, business, domestic, and personal Internet of Things devices become increasingly intelligent, they communicate with each other and share data to help calibrate performance and maximize efficiency. The result, as Sisense CEO Amir Orad wrote , is that every company is now a data company. This is quantitative data.

Statistics 98

Statistics Unstructured Data Data-driven Visualization 98

Corinium

APRIL 25, 2019

Most enterprises in the 21st century regard data as an incredibly valuable asset – Insurance is no exception - to know your customers better, know your market better, operate more efficiently and other business benefits. The protection policy follows the data. This is a much more proactive and scalable model.

Insurance 150

Insurance Risk IoT Cost-Benefit 150

Jet Global

FEBRUARY 14, 2022

Digital technology provides the only realistic way of rendering large volumes of data into a usable form in a practical timeframe. Structuring data in a way that recognizes the importance of tax from the outset is far more efficient than a silo approach and common data models will be key enablers of a more holistic process.”.

Finance 52

Finance Recreation/Entertainment Software Reporting 52