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 113

Recreation/Entertainment Data Lake Data Warehouse Unstructured Data 113

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 103

Unstructured Data Data Lake Prescriptive Analytics Digital Transformation 103

AWS Big Data

MARCH 7, 2023

A data hub contains data at multiple levels of granularity and is often not integrated. It differs from a data lake by offering data that is pre-validated and standardized, allowing for simpler consumption by users. Data hubs and data lakes can coexist in an organization, complementing each other.

Analytics 70

Analytics Data Warehouse Data Lake Metadata 70

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 83

Data Science Data Analytics Prescriptive Analytics Analytics 83

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. You can use simple SQL to analyze structured and semi-structured data, operational databases, and data lakes to deliver the best price/performance at any scale.

Big Data 65

Big Data Data Warehouse Advertising OLAP 65

CIO Business Intelligence

DECEMBER 4, 2023

A modern information lifecycle management approach Today’s ILM approach recognizes the enterprise value of all digitized and enriched assets , avoiding the habituated, narrow reliance ontraditional structured data. When data is stored in a modern, accessible repository, organizations gain newfound capabilities.

Unstructured Data 52

Unstructured Data Data Lake Business Objectives Metadata 52

IBM Big Data Hub

APRIL 25, 2023

In a prior blog , we pointed out that warehouses, known for high-performance data processing for business intelligence, can quickly become expensive for new data and evolving workloads. Similarly, the relational database has been the foundation for data warehousing for as long as data warehousing has been around.

Optimization 57

Optimization Strategy Data Warehouse Cost-Benefit 57

Sisense

APRIL 26, 2020

Structured vs unstructured data. Structured data is far easier for programs to understand, while unstructured data poses a greater challenge. However, both types of data play an important role in data analysis. Structured data. Structured data is organized in tabular format (ie.

Unstructured Data 52

Unstructured Data Data Warehouse Structured Data Data mining 52

CIO Business Intelligence

OCTOBER 25, 2023

The release of intellectual property and non-public information Generative AI tools can make it easy for well-meaning users to leak sensitive and confidential data. Once shared, this data can be fed into the data lakes used to train large language models (LLMs) and can be discovered by other users.

Enterprise 131

Enterprise Risk Manufacturing Finance 131

AWS Big Data

AUGUST 31, 2023

Data warehousing provides a business with several benefits such as advanced business intelligence and data consistency. Amazon Redshift is a fast, fully managed, cloud data warehouse that allows you to process and run your complex SQL analytics workloads on structured and semi-structured data.

Data Warehouse 81

Data Warehouse Data-driven Testing Business Intelligence 81

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

NOVEMBER 9, 2023

This process has been scheduled to run daily, ensuring a consistent batch of fresh data for analysis. AWS Glue – AWS Glue is used to load files into Amazon Redshift through the S3 data lake. You can also use features like auto-copy from Amazon S3 (feature under preview) to ingest data from Amazon S3 to Amazon Redshift.

Data Warehouse 103

Data Warehouse Testing Data Quality Reporting 103

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. But when it’s dirty, stagnant, or hard to unleash, your business will suffer. Benefits of a Data Lake.

Data Lake 52

Data Lake Metadata Data Warehouse Data Governance 52

AWS Big Data

JANUARY 22, 2024

The majority of data produced by these accounts is used downstream for business intelligence (BI) purposes and in Amazon Athena , by hundreds of business users every day. The solution Acast implemented is a data mesh, architected on AWS.

Data-driven 83

Data-driven Advertising Metadata Data Architecture 83

Octopai

MAY 30, 2019

If the point of Business Intelligence (BI) data governance is to leverage your datasets to support information transparency and decision-making, then it’s fair to say that the data catalog is key for your BI strategy. At least, as far as data analysis is concerned. The Benefits of Structured Data Catalogs.

Metadata 40

Metadata Data Governance Data Lake IoT 40

Sisense

OCTOBER 6, 2020

Most commonly, we think of data as numbers that show information such as sales figures, marketing data, payroll totals, financial statistics, and other data that can be counted and measured objectively. This is quantitative data. It’s “hard,” structured data that answers questions such as “how many?”

Statistics 98

Statistics Unstructured Data Data-driven Visualization 98

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 139

Data Lake Data Warehouse Unstructured Data Business Intelligence 139

CIO Business Intelligence

MARCH 9, 2022

As a result, users can easily find what they need, and organizations avoid the operational and cost burdens of storing unneeded or duplicate data copies. Newer data lakes are highly scalable and can ingest structured and semi-structured data along with unstructured data like text, images, video, and audio.

Data Lake 108

Data Lake Unstructured Data Data Warehouse Data Quality 108

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

APRIL 4, 2023

Let’s look at the data architecture journey to understand why and how data lakehouses help to solve complexity, value and security. Traditionally, data warehouses have stored curated, structured data to support analytics and business intelligence, with fast, easy access to data.

Data Architecture 52

Data Architecture Data Lake Data Warehouse Cost-Benefit 52

Peter James Thomas

AUGUST 29, 2018

I have since run and driven transformation in Reference Data, Master Data , KYC [3] , Customer Data, Data Warehousing and more recently Data Lakes and Analytics , constantly building experience and capability in the Data Governance , Quality and data services domains, both inside banks, as a consultant and as a vendor.

Data-driven 61

Data-driven Cost-Benefit Metadata Technology 61

CIO Business Intelligence

OCTOBER 18, 2022

She decided to bring Resultant in to assist, starting with the firm’s strategic data assessment (SDA) framework, which evaluates a client’s data challenges in terms of people and processes, data models and structures, data architecture and platforms, visual analytics and reporting, and advanced analytics.

Data Transformation 141

Data Transformation Consulting Data Lake Reporting 141

Alation

JULY 19, 2022

Finally, a data catalog can help data scientists find answers to their questions (and avoid re-asking questions that have already been answered). Modern data catalogs surface a wide range of data asset types. Data scientists often have different requirements for a data catalog than data analysts.

Metadata 59

Metadata Data Quality Statistics Data Science 59

CIO Business Intelligence

JULY 29, 2022

Aimee Oz, a software development engineer at Capital Group, started in 2021 as an intern and participated in the data engineering bootcamp that was offered to all new team members. The bootcamp broadened my understanding of key concepts in data engineering. Investing in future leaders.

Data Lake 94

Data Lake Software Data Processing Structured Data 94

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! Dig into AI.

Modeling 84

Modeling Big Data IoT Data Warehouse 84

CIO Business Intelligence

MARCH 6, 2023

Advancements in analytics and AI as well as support for unstructured data in centralized data lakes are key benefits of doing business in the cloud, and Shutterstock is capitalizing on its cloud foundation, creating new revenue streams and business models using the cloud and data lakes as key components of its innovation platform.

Data Lake 68

Data Lake Cost-Benefit Recreation/Entertainment Experimentation 68