Alation

OCTOBER 21, 2021

Data Swamp vs Data Lake. When you imagine a lake, it’s likely an idyllic image of a tree-ringed body of reflective water amid singing birds and dabbling ducks. I’ll take the lake, thank you very much. Many organizations have built a data lake to solve their data storage, access, and utilization challenges.

Data Lake 52

Data Lake Metadata Data Warehouse Data Governance 52

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 77

Data Lake Data Warehouse Sales Data-driven 77

Sisense

JUNE 30, 2020

In a world increasingly dominated by data, users of all kinds are gathering, managing, visualizing, and analyzing data in a wide variety of ways. One of the downsides of the role that data now plays in the modern business world is that users can be overloaded with jargon and tech-speak, which can be overwhelming.

Visualization 93

Visualization Analytics Dashboards Data-driven 93

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.

Enterprise 52

Enterprise Knowledge Discovery Risk Data-driven 52

CIO Business Intelligence

OCTOBER 18, 2022

Noel had already established a relationship with consulting firm Resultant through a smaller data visualization project. Resultant recommended a new, on-prem data infrastructure, complete with data lakes to provide stake holders with a better way to manage data reliability, accuracy, and timeliness.

Data Transformation 141

Data Transformation Consulting Data Lake Reporting 141

CIO Business Intelligence

AUGUST 18, 2022

Previously, Walgreens was attempting to perform that task with its data lake but faced two significant obstacles: cost and time. Those challenges are well-known to many organizations as they have sought to obtain analytical knowledge from their vast amounts of data. Lakehouses redeem the failures of some data lakes.

Data Lake 140

Data Lake Data Warehouse Unstructured Data Business Intelligence 140

AWS Big Data

MARCH 26, 2024

Without C360, businesses face missed opportunities, inaccurate reports, and disjointed customer experiences, leading to customer churn. You can use the same capabilities to serve financial reporting, measure operational performance, or even monetize data assets. QuickSight offers scalable, serverless visualization capabilities.

Data Strategy 68

Data Strategy Strategy Data Warehouse Prescriptive Analytics 68

FineReport

APRIL 11, 2023

Every user can now create interactive reports and utilize data visualization to disseminate knowledge to both internal and external stakeholders. These dashboards are more interactive than traditional static reports, allowing users to access underlying data for further analysis.

Dashboards 40

Dashboards Business Intelligence Cost-Benefit Metrics 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

Cloudera

JULY 26, 2021

Auditabily: Data security and compliance constituents need to understand how data changes, where it originates from and how data consumers interact with it. a technology choice such as Spark Streaming is overly focused on throughput at the expense of latency) or data formats (e.g., data warehousing).

Strategy 114

Strategy Marketing Unstructured Data Data Science 114

Sisense

MAY 11, 2021

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. According to a recent survey conducted by IDC , 43% of respondents were drawing intelligence from 10 to 30 data sources in 2020, with a jump to 64% in 2021! Enriching (e.g.,

Modeling 84

Modeling Big Data IoT Data Warehouse 84

AWS Big Data

JUNE 21, 2023

The challenge comes when we need to ask more complex questions of our data, for example, what was the year-on-year quarterly sales growth by product broken down by country? The case for a data warehouse A data warehouse is ideally suited to answer OLAP queries. To house our data, we need to define a data model.

Data Warehouse 80

Data Warehouse Data Lake OLAP Cost-Benefit 80

AWS Big Data

DECEMBER 21, 2023

The data products used inside the company include insights from user journeys, operational reports, and marketing campaign results, among others. The data platform serves on average 60 thousand queries per day. The data volume is in double-digit TBs with steady growth as business and data sources evolve.

Data Lake 89

Data Lake Data Warehouse B2B Data-driven 89