IBM Big Data Hub

APRIL 9, 2024

This allows the Masters to scale analytics and AI wherever their data resides, through open formats and integration with existing databases and tools. “Hole distances and pin positions vary from round to round and year to year; these factors are important as we stage the data.”

Management 87

Management IT Machine Learning Metrics 87

AWS Big Data

MARCH 7, 2023

This post provides guidance on how to build scalable analytical solutions for gaming industry use cases using Amazon Redshift Serverless. This post also discusses the art of the possible with newer innovations in AWS services around streaming, machine learning (ML), data sharing, and serverless capabilities.

Analytics 70

Analytics Data Warehouse Data Lake Metadata 70

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 82

Data Lake Big Data Consulting Data Warehouse 82

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 116

Recreation/Entertainment Data Lake Data Warehouse Unstructured Data 116

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 offensive side? The company’s Findability.ai

Unstructured Data 105

Unstructured Data Data Lake Prescriptive Analytics Digital Transformation 105

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. To understand the best ways to make API calls via Apache Flink, refer to Common streaming data enrichment patterns in Amazon Kinesis Data Analytics for Apache Flink.

Data Lake 88

Data Lake Unstructured Data Management Modeling 88

AWS Big Data

FEBRUARY 7, 2023

In the data analytics space, organizations often deal with many tables in different databases and file formats to hold data for different business functions. Apache Hudi supports ACID transactions and CRUD operations on a data lake. It uses the native support for Apache Hudi on AWS Glue for Apache Spark.

Data Lake 71

Data Lake Testing Big Data Structured Data 71

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. To do so, Presto and Spark need to readily work with existing and modern data warehouse infrastructures. Some use case examples will help.

Optimization 57

Optimization Strategy Data Warehouse Cost-Benefit 57

IBM Big Data Hub

JULY 5, 2022

Db2’s decades of innovation and expertise running the most demanding transactional, analytical, and operational workloads have culminated today in the 2022 Gartner Peer Insights Customers’ Choice distinction for Cloud Database Management Systems. . Nedbank builds a scalable data warehouse architecture . Anywhere deployment .

Data Lake 96

Data Lake Data Warehouse Publishing Structured Data 96

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. This facilitates collaboration across isolated clusters, allowing data to be shared for innovation and analytic services.

Testing 98

Testing Data Warehouse Metrics Cost-Benefit 98

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

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 75

Data Lake Data Warehouse Sales Data-driven 75

AWS Big Data

JULY 19, 2023

We’ve seen that there is a demand to design applications that enable data to be portable across cloud environments and give you the ability to derive insights from one or more data sources. With this connector, you can bring the data from Google Cloud Storage to Amazon S3.

Big Data 81

Big Data Software Consulting Unstructured Data 81

AWS Big Data

MARCH 27, 2024

Achieving this will also improve general public health through better and more timely interventions, identify health risks through predictive analytics, and accelerate the research and development process. This will be your online transaction processing (OLTP) data store for transactional data.

Data Analytics 89

Data Analytics Analytics Data Warehouse Data Lake 89

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

Gartner predicts that graph technologies will be used in 80% of data and analytics innovations by 2025, up from 10% in 2021. Graphs boost knowledge discovery and efficient data-driven analytics to understand a company’s relationship with customers and personalize marketing, products, and services.

Enterprise 52

Enterprise Knowledge Discovery Risk Data-driven 52

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 90

Data Warehouse Data Lake Analytics Data Science 90

BizAcuity

MARCH 1, 2019

Traditional methods of analyzing structured data are not designed to efficiently process these large amounts of real-time data that is collected from IoT devices. This is where AI-based analysis and response play a critical role in extracting optimal value from the data. Bringing the power of AI to IoT.

IoT 56

IoT Internet of Things Big Data Data-driven 56

Alation

FEBRUARY 20, 2020

Architecturally the introduction of Hadoop, a file system designed to store massive amounts of data, radically affected the cost model of data. Organizationally the innovation of self-service analytics, pioneered by Tableau and Qlik, fundamentally transformed the user model for data analysis. The Rise of the Data Catalog.

Data Lake 52

Data Lake Metadata Structured Data Big Data 52

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

AWS Big Data

OCTOBER 25, 2023

By some estimates, unstructured data can make up to 80–90% of all new enterprise data and is growing many times faster than structured data. After decades of digitizing everything in your enterprise, you may have an enormous amount of data, but with dormant value. These services write the output to a data lake.

Unstructured Data 117

Unstructured Data Metadata Management Analytics 117

IBM Big Data Hub

APRIL 24, 2023

Data warehouse is the base architecture for artificial intelligence and machine learning (AI/ML) solutions as well. Benefits of new data warehousing technology Everything is data, regardless of whether it’s structured, semi-structured, or unstructured.

Data Warehouse 98

Data Warehouse Data Lake Cost-Benefit Enterprise 98

AWS Big Data

DECEMBER 15, 2023

Even after identification, it’s cumbersome to implement redaction, masking, or encryption of sensitive data at scale. In this post, we provide an automated solution to detect PII data in Amazon Redshift using AWS Glue. For our solution, we use Amazon Redshift to store the data.

Data Lake 101

Data Lake Data Warehouse Big Data Structured Data 101

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. Analytical and transactional worlds come together.

Data Lake 52

Data Lake Data Warehouse Data-driven Metadata 52

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 111

Data Lake Unstructured Data Data Warehouse Data Quality 111

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

APRIL 19, 2023

With the right analytics approach, this is possible. 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.

Data Warehouse 55

Data Warehouse Data Lake Unstructured Data Optimization 55

Sisense

JUNE 30, 2020

Everyone wants to get more out of their data, but how exactly to do that can leave you scratching your head. Our BI Best Practices demystify the analytics world and empower you with actionable how-to guidance. When BI and analytics users want to see analytics results, and learn from them quickly, they rely on data visualizations.

Visualization 93

Visualization Analytics Dashboards Data-driven 93

Alation

MAY 16, 2023

Data is a valuable resource, especially in the world of business. A McKinsey survey found that companies that use customer analytics intensively are 19 times higher to achieve above-average profitability. But with the sheer amount of data continually increasing, how can a business make sense of it? Robust data pipelines.

Data Lake 69

Data Lake Data Governance Data Warehouse Data Processing 69

Alation

MAY 16, 2023

Data is a valuable resource, especially in the world of business. A McKinsey survey found that companies that use customer analytics intensively are 19 times higher to achieve above-average profitability. But with the sheer amount of data continually increasing, how can a business make sense of it? Robust data pipelines.

Data Lake 40

Data Lake Data Governance Data Warehouse Data Processing 40

AWS Big Data

OCTOBER 2, 2023

For a deeper exploration on configuring and using streaming ingestion in Amazon Redshift , refer to Real-time analytics with Amazon Redshift streaming ingestion. In addition to this approach, the Amazon Redshift JSON functions allow storing and analyzing the JSON data in its original state using the adaptable SUPER data type.

Cost-Benefit 84

Cost-Benefit Metadata Structured Data Management 84

Corinium

APRIL 25, 2019

Ahead of the Chief Data Analytics Officers & Influencers, Insurance event we caught up with Dominic Sartorio, Senior Vice President for Products & Development, Protegrity to discuss how the industry is evolving. Why should Chief Data & Analytics Officers care about data security?

Insurance 150

Insurance Risk IoT Cost-Benefit 150

AWS Big Data

MARCH 26, 2024

In this post, we discuss how you can use purpose-built AWS services to create an end-to-end data strategy for C360 to unify and govern customer data that address these challenges. We recommend building your data strategy around five pillars of C360, as shown in the following figure.

Data Strategy 67

Data Strategy Strategy Data Warehouse Prescriptive Analytics 67

Sisense

JULY 22, 2020

At Sisense, we’re dedicated to making this complex task simple, putting power in the hands of the builders of business data and strategy, and providing insights for everyone. The launch of the Google Sheets analytics template illustrates this. Understanding how data becomes insights. Connect tables.

Slice and Dice 98

Slice and Dice Digital Transformation Data Warehouse Data Lake 98

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

Alation

JULY 19, 2022

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. Obstacles, such as user roles, permissions, and approval request prevent speedy data access.

Metadata 59

Metadata Data Quality Statistics Data Science 59