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 119

Recreation/Entertainment Data Lake Data Warehouse Unstructured Data 119

IBM Big Data Hub

APRIL 25, 2023

We also made the case that query and reporting, provided by big data engines such as Presto, need to work with the Spark infrastructure framework to support advanced analytics and complex enterprise data decision-making. To do so, Presto and Spark need to readily work with existing and modern data warehouse infrastructures.

Optimization 56

Optimization Strategy Data Warehouse Cost-Benefit 56

AWS Big Data

MARCH 7, 2023

Analytics reference architecture for gaming organizations In this section, we discuss how gaming organizations can use a data hub architecture to address the analytical needs of an enterprise, which requires the same data at multiple levels of granularity and different formats, and is standardized for faster consumption.

Analytics 73

Analytics Data Warehouse Data Lake Metadata 73

CIO Business Intelligence

FEBRUARY 16, 2023

Selling the value of data transformation Iyengar and his team are 18 months into a three- to five-year journey that started by building out the data layer — corralling data sources such as ERP, CRM, and legacy databases into data warehouses for structured data and data lakes for unstructured data.

Unstructured Data 105

Unstructured Data Data Lake Prescriptive Analytics Digital Transformation 105

AWS Big Data

NOVEMBER 9, 2023

It allows users to write data transformation code, run it, and test the output, all within the framework it provides. Use case The Enterprise Data Analytics group of a large jewelry retailer embarked on their cloud journey with AWS in 2021. AWS Glue – AWS Glue is used to load files into Amazon Redshift through the S3 data lake.

Data Warehouse 108

Data Warehouse Testing Data Quality Reporting 108

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

AWS Big Data

MARCH 25, 2024

Amazon DocumentDB (with MongoDB compatibility) is a fast, scalable, highly available, and fully managed enterprise document database service that supports native JSON workloads. With a file system sink connector, Apache Flink jobs can deliver data to Amazon S3 in open format (such as JSON, Avro, Parquet, and more) files as data objects.

Data Lake 93

Data Lake Unstructured Data Management Modeling 93

Jet Global

OCTOBER 30, 2020

Introducing Data Lakes. Microsoft’s next option is called Azure Data Lake Services (ADLS), and it seems to be the company’s favored long-term solution to its D365 F&SCM reporting challenge. Data lake” is a generic term that refers to a fairly new development in the world of big data analytics.

Data Lake 52

Data Lake Unstructured Data Reporting Finance 52

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 80

Data Science Data Analytics Prescriptive Analytics Analytics 80

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. An integrated multicloud data platform .

Data Lake 90

Data Lake Data Warehouse Publishing Structured Data 90

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 79

Data Lake Data Warehouse Sales Data-driven 79

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

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 94

Data Analytics Analytics Data Warehouse Data Lake 94

IBM Big Data Hub

APRIL 24, 2023

Additionally, the increase in online transactions and web traffic generated mountains of data. Enter the modernization of data warehousing solutions. Companies realized that their legacy or enterprise data warehousing solutions could not manage the huge workload.

Data Warehouse 93

Data Warehouse Data Lake Cost-Benefit Enterprise 93

AWS Big Data

DECEMBER 15, 2023

Many companies identify and label PII through manual, time-consuming, and error-prone reviews of their databases, data warehouses and data lakes, thereby rendering their sensitive data unprotected and vulnerable to regulatory penalties and breach incidents. Load data from Amazon S3 to the Redshift data warehouse.

Data Lake 106

Data Lake Data Warehouse Big Data Structured Data 106

IBM Big Data Hub

JANUARY 18, 2023

Data platform architecture has an interesting history. Towards the turn of millennium, enterprises started to realize that the reporting and business intelligence workload required a new solution rather than the transactional applications. A read-optimized platform that can integrate data from multiple applications emerged.

Data Lake 52

Data Lake Data Warehouse Data-driven Metadata 52

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

CIO Business Intelligence

MARCH 9, 2022

Applying artificial intelligence (AI) to data analytics for deeper, better insights and automation is a growing enterprise IT priority. 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.

Data Lake 119

Data Lake Unstructured Data Data Warehouse Data Quality 119

CIO Business Intelligence

APRIL 4, 2023

In order to move AI forward, we need to first build and fortify the foundational layer: data architecture. This architecture is important because, to reap the full benefits of AI, it must be built to scale across an enterprise versus individual AI applications. Constructing the right data architecture cannot be bypassed.

Data Architecture 52

Data Architecture Data Lake Data Warehouse Cost-Benefit 52

AWS Big Data

MARCH 26, 2024

The AWS modern data architecture shows a way to build a purpose-built, secure, and scalable data platform in the cloud. Learn from this to build querying capabilities across your data lake and the data warehouse. Let’s find out what role each of these components play in the context of C360.

Data Strategy 70

Data Strategy Strategy Data Warehouse Prescriptive Analytics 70

Alation

APRIL 6, 2023

Data governance is traditionally applied to structured data assets that are most often found in databases and information systems. Spreadsheets are not typically developed and managed for enterprise use, which opens the door to risk from malicious actors, as well as human errors.

Data Governance 52

Data Governance Metadata Cost-Benefit Structured Data 52

AWS Big Data

JULY 28, 2023

Organizations must comply with these requests provided that there are no legitimate grounds for retaining the personal data, such as legal obligations or contractual requirements. Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. You can contact us with questions.

Snapshot 85

Snapshot Metadata Measurement Data Warehouse 85

Cloudera

SEPTEMBER 12, 2022

First, organizations have a tough time getting their arms around their data. More data is generated in ever wider varieties and in ever more locations. Organizations don’t know what they have anymore and so can’t fully capitalize on it — the majority of data generated goes unused in decision making.

Unstructured Data 72

Unstructured Data Data Architecture Data Lake Snapshot 72

Corinium

APRIL 25, 2019

Why should Chief Data & Analytics Officers care about data security? 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. That’s the reward.

Insurance 150

Insurance Risk IoT Cost-Benefit 150

FineReport

APRIL 11, 2023

Additionally, they provide tabs, pull-down menus, and other navigation features to assist in accessing data. Data Visualizations : Dashboards are configured with a variety of data visualizations such as line and bar charts, bubble charts, heat maps, and scatter plots to show different performance metrics and statistics.

Dashboards 40

Dashboards Business Intelligence Cost-Benefit Metrics 40

Alation

JULY 19, 2022

Data scientists often have different requirements for a data catalog than data analysts. Although there is significant overlap between their workflows, data scientists often rely on raw data stored in a data lake rather than the highly structured data in a data warehouse, which is the realm of the analyst.

Metadata 59

Metadata Data Quality Statistics Data Science 59

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!

Modeling 84

Modeling Big Data IoT Data Warehouse 84

Cloudera

MAY 23, 2024

In modern enterprises, the exponential growth of data means organizational knowledge is distributed across multiple formats, ranging from structured data stores such as data warehouses to multi-format data stores like data lakes. Langchain) and LLM evaluations (e.g.

Management 66

Management Metrics Data Processing Data Lake 66

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