AWS Big Data

NOVEMBER 9, 2023

User-friendly data mart (UFDM) layer – This final layer uses data from the CDS layer to create data mart tables. These are specifically tailored to support BI reports and dashboards as per the business requirements. The goal of this layer is to present the data in a way that is most useful and accessible for end-users.

Data Warehouse 102

Data Warehouse Testing Data Quality Reporting 102

AWS Big Data

MARCH 7, 2023

It includes business intelligence (BI) users, canned and interactive reports, dashboards, data science workloads, Internet of Things (IoT), web apps, and third-party data consumers. Popular consumption entities in many organizations are queries, reports, and data science workloads.

Analytics 70

Analytics Data Warehouse Data Lake Metadata 70

BizAcuity

MARCH 29, 2019

Data lakes are centralized repositories that can store all structured and unstructured data at any desired scale. The power of the data lake lies in the fact that it often is a cost-effective way to store data. Data in healthcare industry can be broadly classified into two sources: clinical data and claims data.

Data Lake 102

Data Lake Unstructured Data Cost-Benefit Data Quality 102

CDW Research Hub

APRIL 20, 2020

Snowflake, a data warehouse built specifically for the cloud, is one popular option. Snowflake helps eliminate many of the common issues data professionals face because it supports structured and semi-structured data, scales massive concurrency without limit, and boasts secure, live data sharing.

Data Warehouse 52

Data Warehouse Consulting Data-driven Structured Data 52

Jet Global

OCTOBER 30, 2020

“Data lake” is a generic term that refers to a fairly new development in the world of big data analytics. Data lakes are oriented toward unstructured data and artificial intelligence. What are unstructured data? First, let’s consider what “structured” data looks like: CustomerID. CustomerName.

Data Lake 52

Data Lake Unstructured Data Reporting Finance 52

AWS Big Data

MARCH 25, 2024

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. OpenSearch Service offers visualization capabilities powered by OpenSearch Dashboards and Kibana (1.5

Data Lake 88

Data Lake Unstructured Data Management Modeling 88

AWS Big Data

JUNE 6, 2023

As the SumUp merchants user journey only starts onsite (with a Sign up or product purchase), but extends to offline card reader transactions or usage of our products from within our app and web dashboard, it is important to combine Digital Analytics data with other (backend) data sources in our Data Lake or DWH.

Analytics 55

Analytics Data Lake Testing Optimization 55

AWS Big Data

APRIL 20, 2023

Customers use Amazon Redshift to run their business-critical analytics on petabytes of structured and semi-structured data. Apache Spark enables you to build applications in a variety of languages, such as Java, Scala, and Python, by accessing the data in your Amazon Redshift data warehouse.

Data Lake 75

Data Lake Data Warehouse Sales Data-driven 75

AWS Big Data

FEBRUARY 20, 2024

With this zero-ETL approach, Amazon Redshift Streaming Ingestion enables you to connect to multiple Kinesis data streams or Amazon Managed Streaming for Apache Kafka (Amazon MSK) data streams and pull data directly to Amazon Redshift without staging data in Amazon Simple Storage Service (Amazon S3).

Visualization 97

Visualization Cost-Benefit Optimization B2B 97

datapine

MAY 27, 2020

Use digital dashboards: When considering the question “what is an analytical report,” it’s important to think about the best medium in terms of usability and presentation. It is possible to structure data across a broad range of spreadsheets, but the final result can be more confusing than productive.

Reporting 245

Reporting Analytics Dashboards Sales 245

AWS Big Data

MARCH 2, 2023

Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. Amazon Redshift enables you to use SQL for analyzing structured and semi-structured data with best price performance along with secure access to the data. Grafana provides a predefined dashboard to visualize database privileges.

Visualization 77

Visualization Dashboards Data Warehouse Metrics 77

IBM Big Data Hub

APRIL 24, 2023

Data warehousing solutions drive business efficiency, build future analysis and predictions, enhance productivity, and improve business success. These solutions categorize and convert data into readable dashboards that anyone in a company can analyze. Companies require additional resources and people to process enterprise data.

Data Warehouse 98

Data Warehouse Data Lake Cost-Benefit Enterprise 98

FineReport

JULY 18, 2022

The features you or your company need are core factors influencing your selection of the data analytics tool. For example, if you want the features of data visualization , such as stunning dashboards and rich charts, business intelligence tools are more suitable for you than a pure programming tool. 15 Best Data Analysis Tools.

Forecasting 52

Forecasting Dashboards Visualization Statistics 52

AWS Big Data

MARCH 27, 2024

The Data Catalog objects are listed under the awsdatacatalog database. FHIR data stored in AWS HealthLake is highly nested. To learn about how to un-nest semi-structured data with Amazon Redshift, see Tutorial: Querying nested data with Amazon Redshift Spectrum. Use the following query to flatten data: SELECT data."

Data Analytics 89

Data Analytics Analytics Data Warehouse Data Lake 89

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. Changing all interleaved key tables on the producer cluster to compound sortkey tables to seamlessly transition data.

Data Warehouse 90

Data Warehouse Data Lake Analytics Data Science 90

Rocket-Powered Data Science

JULY 14, 2023

The results showed that (among those surveyed) approximately 90% of enterprise analytics applications are being built on tabular data. The ease with which such structured data can be stored, understood, indexed, searched, accessed, and incorporated into business models could explain this high percentage.

Analytics 165

Analytics Internet of Things Prescriptive Analytics Data Science 165

FineReport

JUNE 24, 2021

Then, once it has turned the raw, unstructured data into a structured data set, it can analyze that data. BI software solutions often support multiple data source connections. Allowing business personnel to obtain the data they need conveniently is the basis for fast-responsive analysis.

Business Intelligence 84

Business Intelligence OLAP Data mining Visualization 84

AWS Big Data

FEBRUARY 22, 2023

The data lake implemented by Ruparupa uses Amazon S3 as the storage platform, AWS Database Migration Service (AWS DMS) as the ingestion tool, AWS Glue as the ETL (extract, transform, and load) tool, and QuickSight for analytic dashboards. The audience of these few reports was limited—a maximum of 20 people from management.

Data Lake 52

Data Lake Dashboards Cost-Benefit Metadata 52

AWS Big Data

MARCH 26, 2024

The following diagram shows a sample C360 dashboard built on Amazon QuickSight. You can benefit from its ML integrations for automated insights like forecasting and anomaly detection or natural language querying with Amazon Q in QuickSight , direct data connectivity from various sources, and pay-per-session pricing.

Data Strategy 67

Data Strategy Strategy Data Warehouse Prescriptive Analytics 67

FineReport

FEBRUARY 5, 2020

Both the investment community and the IT circle are paying close attention to big data and business intelligence. Overall, as users’ data sources become more extensive, their preferences for BI are changing. They prefer self-service development, interactive dashboards, and self-service data exploration.

Metadata 98

Metadata Dashboards Informatics Visualization 98

Sisense

JULY 22, 2020

They hold structured data from relational databases (rows and columns), semi-structured data ( CSV , logs, XML , JSON ), unstructured data (emails, documents, PDFs), and binary data (images, audio , video). Sisense provides instant access to your cloud data warehouses. Building dashboards and widgets.

Slice and Dice 98

Slice and Dice Digital Transformation Data Warehouse Data Lake 98

CIO Business Intelligence

JUNE 14, 2023

Big data exploded onto the scene in the mid-2000s and has continued to grow ever since. Today, the data is even bigger, and managing these massive volumes of data presents a new challenge for many organizations. Even if you live and breathe tech every day, it’s difficult to conceptualize how big “big” really is.

Unstructured Data 64

Unstructured Data IT Manufacturing Visualization 64

Sisense

MAY 11, 2021

We’re going to nerd out for a minute and dig into the evolving architecture of Sisense to illustrate some elements of the data modeling process: Historically, the data modeling process that Sisense recommended was to structure data mainly to support the BI and analytics capabilities/users. Dig into AI.

Modeling 84

Modeling Big Data IoT Data Warehouse 84

IBM Big Data Hub

JUNE 26, 2023

Yanfeng Auto has previously deployed an open-source Kafka cluster in each branch factory to extract data from multiple real-time production data in its MES system and provide them to the MI Kanban (Dashboard) System of each factory for query and display. However, this open-source system poses multiple operational complexities.

Manufacturing 66

Manufacturing Software Optimization Digital Transformation 66

AWS Big Data

JULY 12, 2023

Etleap integrates key Amazon Redshift features into its product, such as streaming ingestion , Redshift Serverless , and data sharing. In Etleap, pre-load transformations are primarily used for cleaning and structuring data, whereas post-load SQL transformations enable multi-table joins and dataset aggregations.

Data Warehouse 52

Data Warehouse Modeling Dashboards Data Lake 52

Cloudera

SEPTEMBER 6, 2018

The solution combines Cloudera Enterprise , the scalable distributed platform for big data, machine learning, and analytics, with riskCanvas , the financial crime software suite from Booz Allen Hamilton. It supports a variety of storage engines that can handle raw files, structured data (tables), and unstructured data.

Machine Learning 40

Machine Learning Risk Big Data Unstructured Data 40

CDW Research Hub

DECEMBER 4, 2019

Cloud-based data warehouses can also perform complex analytical queries much faster due to the use of massively parallel processing (MPP), which uses multiple processors—each with its own operating system and memory—to simultaneously perform a set of coordinated computations.

Data Warehouse 52

Data Warehouse Data mining Data Lake Dashboards 52

AWS Big Data

FEBRUARY 21, 2023

Business intelligence (BI) with dashboards, reports, and analytics remains one of the most popular use cases for data and analytics. Toucan natively integrates with Redshift Serverless, which enables you to deploy a scalable data stack in minutes without the need to manage any infrastructure component.

Visualization 52

Visualization Dashboards Data Warehouse Cost-Benefit 52

AWS Big Data

APRIL 19, 2023

Different departments within an organization can place data in a data lake or within their data warehouse depending on the type of data and usage patterns of that department. They were able to use Amazon Redshift Serverless to serve their key stakeholders with dashboards with financial data for quick decision-making.

Data Warehouse 55

Data Warehouse Data Lake Unstructured Data Optimization 55

Cloudera

APRIL 1, 2024

This recognition underscores Cloudera’s commitment to continuous customer innovation and validates our ability to foresee future data and AI trends, and our strategy in shaping the future of data management. Cloudera, a leader in big data analytics, provides a unified Data Platform for data management, AI, and analytics.

Unstructured Data 100

Unstructured Data Cost-Benefit Metadata Machine Learning 100