CIO Business Intelligence

FEBRUARY 16, 2023

My vision is that I can give the keys to my businesses to manage their data and run their data on their own, as opposed to the Data & Tech team being at the center and helping them out,” says Iyengar, director of Data & Tech at Straumann Group North America. The company’s Findability.ai

Unstructured Data 105

Unstructured Data Data Lake Prescriptive Analytics Digital Transformation 105

AWS Big Data

OCTOBER 20, 2023

Today, we are pleased to announce new AWS Glue connectors for Azure Blob Storage and Azure Data Lake Storage that allow you to move data bi-directionally between Azure Blob Storage, Azure Data Lake Storage, and Amazon Simple Storage Service (Amazon S3). option("header","true").load("wasbs://yourblob@youraccountname.blob.core.windows.net/loadingtest-input/100mb")

Data Lake 80

Data Lake Big Data Consulting Data Warehouse 80

IBM Big Data Hub

APRIL 25, 2023

To do so, Presto and Spark need to readily work with existing and modern data warehouse infrastructures. Now, let’s chat about why data warehouse optimization is a key value of a data lakehouse strategy. To effectively use raw data, it often needs to be curated within a data warehouse.

Optimization 57

Optimization Strategy Data Warehouse Cost-Benefit 57

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 82

Data Science Data Analytics Prescriptive Analytics Analytics 82

AWS Big Data

MARCH 7, 2023

It covers how to use a conceptual, logical architecture for some of the most popular gaming industry use cases like event analysis, in-game purchase recommendations, measuring player satisfaction, telemetry data analysis, and more. A data hub contains data at multiple levels of granularity and is often not integrated.

Analytics 68

Analytics Data Warehouse Data Lake Metadata 68

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

MARCH 25, 2024

Foundation models (FMs) are large machine learning (ML) models trained on a broad spectrum of unlabeled and generalized datasets. 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.

Data Lake 86

Data Lake Unstructured Data Management Modeling 86

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. The first diagram illustrates the architecture before using data sharing.

Testing 96

Testing Data Warehouse Metrics Cost-Benefit 96

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. Vektis improves healthcare quality through data .

Data Lake 93

Data Lake Data Warehouse Publishing Structured Data 93

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 is a popular framework that you can use to build applications for use cases such as ETL (extract, transform, and load), interactive analytics, and machine learning (ML).

Data Lake 74

Data Lake Data Warehouse Sales Data-driven 74

AWS Big Data

APRIL 19, 2023

In this post, we look at three key challenges that customers face with growing data and how a modern data warehouse and analytics system like Amazon Redshift can meet these challenges across industries and segments. This performance innovation allows Nasdaq to have a multi-use data lake between teams.

Data Warehouse 55

Data Warehouse Data Lake Unstructured Data Optimization 55

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

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

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

IBM Big Data Hub

APRIL 24, 2023

Data is reported from one central repository, enabling management to draw more meaningful business insights and make faster, better decisions. By running reports on historical data, a data warehouse can clarify what systems and processes are working and what methods need improvement.

Data Warehouse 95

Data Warehouse Data Lake Cost-Benefit Enterprise 95

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 87

Data Analytics Analytics Data Warehouse Data Lake 87

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. These upstream data sources constitute the data producer components.

Data Warehouse 88

Data Warehouse Data Lake Analytics Data Science 88

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 99

Data Lake Data Warehouse Big Data Structured Data 99

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

FEBRUARY 22, 2023

In this post, we show how Ruparupa implemented an incrementally updated data lake to get insights into their business using Amazon Simple Storage Service (Amazon S3), AWS Glue , Apache Hudi , and Amazon QuickSight. An AWS Glue ETL job, using the Apache Hudi connector, updates the S3 data lake hourly with incremental data.

Data Lake 52

Data Lake Dashboards Cost-Benefit Metadata 52

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 109

Data Lake Unstructured Data Data Warehouse Data Quality 109

IBM Big Data Hub

JANUARY 18, 2023

In another decade, the internet and mobile started the generate data of unforeseen volume, variety and velocity. It required a different data platform solution. Hence, Data Lake emerged, which handles unstructured and structured data with huge volume. Data lakehouse was created to solve these problems.

Data Lake 52

Data Lake Data Warehouse Data-driven Metadata 52

Alation

MAY 16, 2023

Data Integration A data pipeline can be used to gather data from various disparate sources in one data store. This makes it easier to compare and contrast information and provides organizations with a unified view of their data.

Data Lake 69

Data Lake Data Governance Data Warehouse Data Processing 69

Alation

MAY 16, 2023

Data Integration A data pipeline can be used to gather data from various disparate sources in one data store. This makes it easier to compare and contrast information and provides organizations with a unified view of their data.

Data Lake 40

Data Lake Data Governance Data Warehouse Data Processing 40

AWS Big Data

MARCH 26, 2024

This can be achieved using AWS Entity Resolution , which enables using rules and machine learning (ML) techniques to match records and resolve identities. The AWS modern data architecture shows a way to build a purpose-built, secure, and scalable data platform in the cloud.

Data Strategy 67

Data Strategy Strategy Data Warehouse Prescriptive Analytics 67

CDW Research Hub

DECEMBER 4, 2019

There are many benefits of using a cloud-based data warehouse, and the market for cloud-based data warehouses is growing as organizations realize the value of making the switch from an on-premises data warehouse.

Data Warehouse 52

Data Warehouse Data mining Data Lake Dashboards 52

Sisense

JULY 22, 2020

The trend has been towards using cloud-based applications and tools for different functions, such as Salesforce for sales, Marketo for marketing automation, and large-scale data storage like AWS or data lakes such as Amazon S3 , Hadoop and Microsoft Azure. Sisense provides instant access to your cloud data warehouses.

Slice and Dice 98

Slice and Dice Digital Transformation Data Warehouse Data Lake 98

Corinium

APRIL 25, 2019

I’ve found many IT as well as Business leaders have a mental model of data in that it is simply part of, or belongs to, a specific database or application, and thus they falsely conclude that just procuring a tool to protect that given environment will sufficiently protect that data. In data-driven organizations, data is flowing.

Insurance 150

Insurance Risk IoT Cost-Benefit 150

Alation

JULY 19, 2022

Across the country, data scientists have an unemployment rate of 2% and command an average salary of nearly $100,000. As they attempt to put machine learning models into production, data science teams encounter many of the same hurdles that plagued data analytics teams in years past: Finding trusted, valuable data is time-consuming.

Metadata 59

Metadata Data Quality Statistics Data Science 59

Sisense

JUNE 30, 2020

When BI and analytics users want to see analytics results, and learn from them quickly, they rely on data visualizations. Visua l analytics does the “heavy lifting” with data, by using a variety of processes — mechanical, algorithms, machine learning , natural language processing, etc — to identify and reveal patterns and trends.

Visualization 93

Visualization Analytics Dashboards Data-driven 93

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

AWS Big Data

JUNE 21, 2023

These types of queries are suited for a data warehouse. The goal of a data warehouse is to enable businesses to analyze their data fast; this is important because it means they are able to gain valuable insights in a timely manner. Amazon Redshift is fully managed, scalable, cloud data warehouse.

Data Warehouse 76

Data Warehouse Data Lake OLAP Cost-Benefit 76

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 64

Big Data Data Warehouse Advertising OLAP 64