datapine

MAY 9, 2019

“Without big data, you are blind and deaf and in the middle of a freeway.” – Geoffrey Moore, management consultant, and author. In a world dominated by data, it’s more important than ever for businesses to understand how to extract every drop of value from the raft of digital insights available at their fingertips.

Business Intelligence 270

Business Intelligence Dashboards Data Warehouse Sales 270

Jet Global

NOVEMBER 5, 2020

OLAP reporting has traditionally relied on a data warehouse. Again, this entails creating a copy of the transactional data in the ERP system, but it also involves some preprocessing of data into so-called “cubes” so that you can retrieve aggregate totals and present them much faster. Azure Data Lakes are complicated.

Data Lake 98

Data Lake OLAP Data Warehouse Unstructured Data 98

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 84

Data Science Data Analytics Prescriptive Analytics Analytics 84

AWS Big Data

MARCH 7, 2023

Data lakes are more focused around storing and maintaining all the data in an organization in one place. And unlike data warehouses, which are primarily analytical stores, a data hub is a combination of all types of repositories—analytical, transactional, operational, reference, and data I/O services, along with governance processes.

Analytics 68

Analytics Data Warehouse Data Lake Metadata 68

AWS Big Data

NOVEMBER 9, 2023

The aim was to bolster their analytical capabilities and improve data accessibility while ensuring a quick time to market and high data quality, all with low total cost of ownership (TCO) and no need for additional tools or licenses. AWS Glue is a fully managed ETL service that makes it easy to prepare and load data for analysis.

Data Warehouse 100

Data Warehouse Testing Data Quality Reporting 100

IBM Big Data Hub

JULY 5, 2022

In today’s world of complex data architectures and emerging technologies, databases can sometimes be undervalued and unrecognized. IBM has been the pioneer in paving the way for data management technologies and advancements for decades, from the first commercial database to quantum computing systems.

Data Lake 97

Data Lake Data Warehouse Publishing Structured Data 97

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. The Stripe Data Pipeline is powered by the data sharing capability of Amazon Redshift.

Data Warehouse 55

Data Warehouse Data Lake Unstructured Data Optimization 55

Jet Global

OCTOBER 30, 2020

“Data lake” is a generic term that refers to a fairly new development in the world of big data analytics. Data lakes are oriented toward unstructured data and artificial intelligence. What are unstructured data? First, let’s consider what “structured” data looks like: CustomerID. CustomerName.

Data Lake 52

Data Lake Unstructured Data Reporting Finance 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 73

Data Lake Data Warehouse Sales Data-driven 73

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

AWS Big Data

MARCH 25, 2024

Studio notebooks seamlessly combine these technologies to make advanced analytics on data streams accessible to developers of all skill sets. 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

IBM Big Data Hub

APRIL 24, 2023

Innovative organizations sought modern solutions to manage larger data capacities and attain secure storage solutions, helping them meet consumer demands. One of these advances included the accelerated adoption of modernized data warehousing technologies. Modern data warehousing technology can handle all data forms.

Data Warehouse 99

Data Warehouse Data Lake Cost-Benefit Enterprise 99

AWS Big Data

JUNE 6, 2023

SumUp is a leading global financial technology company driven by the purpose of leveling the playing field for small businesses. Unless, of course, the rest of their data also resides in the Google Cloud. AWS Glue gave us a cost-efficient option to migrate the data and we further optimized storage cost by pruning cold data.

Analytics 55

Analytics Data Lake Testing Optimization 55

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 119

Data Lake Unstructured Data Data Warehouse Data Quality 119

CIO Business Intelligence

AUGUST 18, 2022

To find out, he queried Walgreens’ data lakehouse, implemented with Databricks technology on Microsoft Azure. “We For Guadagno, the need to match vaccine availability with patient demand came at the right moment, technologically speaking. Enter the data lakehouse. Under Guadagno, the Deerfield, Ill.

Data Lake 140

Data Lake Data Warehouse Unstructured Data Business Intelligence 140

FineReport

JUNE 24, 2021

Data is the key to gaining great insights for most businesses, but it is also one of the biggest obstacles. Originally, Excel has always been the “solution” for various reporting and data needs. Technicals such as data warehouse, online analytical processing (OLAP) tools, and data mining are often binding.

Business Intelligence 84

Business Intelligence OLAP Data mining Visualization 84

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

AWS Big Data

JULY 12, 2023

Introduction to Amazon Redshift Amazon Redshift is a fast, fully-managed, self-learning, self-tuning, petabyte-scale, ANSI-SQL compatible, and secure cloud data warehouse. Thousands of customers use Amazon Redshift to analyze exabytes of data and run complex analytical queries.

Data Warehouse 52

Data Warehouse Modeling Dashboards Data Lake 52

AWS Big Data

FEBRUARY 20, 2024

To overcome these challenges, businesses need a solution that can provide near-real-time analytics on transactional data with services that don’t lead to latent processing and bloat from managing the pipeline. The elasticity of Kinesis Data Streams enables you to scale the stream up or down, so you never lose data records before they expire.

Visualization 95

Visualization Cost-Benefit Optimization B2B 95

AWS Big Data

OCTOBER 18, 2023

Apache Hive is a distributed, fault-tolerant data warehouse system that enables analytics at a massive scale. Spark SQL is an Apache Spark module for structured data processing. About the authors Amit Maindola is a Senior Data Architect focused on big data and analytics at Amazon Web Services.

Big Data 77

Big Data Data Processing Interactive Testing 77

Sisense

MAY 11, 2021

We’re going to nerd out for a minute and dig into the evolving architecture of Sisense to illustrate some elements of the data modeling process: Historically, the data modeling process that Sisense recommended was to structure data mainly to support the BI and analytics capabilities/users. Dig into AI.

Modeling 84

Modeling Big Data IoT Data Warehouse 84

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. To learn more, contact us for more information or email me at tom.williams@siriuscom.com.

Data Warehouse 52

Data Warehouse Data mining Data Lake Dashboards 52

CDW Research Hub

OCTOBER 12, 2021

One of the biggest obstacles to this needed agility is poorly integrated data, which results in five key challenges: The inability to support a logical data warehouse architecture to enable advanced analytics. Unreliable Data as a Service (DaaS) implementations. Silos within big data implementations.

Data Warehouse 52

Data Warehouse Big Data Data Architecture Cost-Benefit 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.

Snapshot 79

Snapshot Metadata Measurement Data Warehouse 79

AWS Big Data

FEBRUARY 22, 2023

Data analytic challenges As an ecommerce company, Ruparupa produces a lot of data from their ecommerce website, their inventory systems, and distribution and finance applications. The data can be structured data from existing systems, and can also be unstructured or semi-structured data from their customer interactions.

Data Lake 52

Data Lake Dashboards Cost-Benefit Metadata 52

AWS Big Data

MARCH 28, 2023

In a data warehouse, a dimension is a structure that categorizes facts and measures in order to enable users to answer business questions. Vijay Velpula is a Data Architect with AWS Professional Services. He helps customers implement Big Data and Analytics Solutions.

Data Lake 68

Data Lake Testing Snapshot Sales 68

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

AWS Big Data

FEBRUARY 21, 2023

Toucan natively integrates with Redshift Serverless, which enables you to deploy a scalable data stack in minutes without the need to manage any infrastructure component. Amazon Redshift is a fully managed cloud data warehouse service that enables you to analyze large amounts of structured and semi-structured data.

Visualization 52

Visualization Dashboards Data Warehouse Cost-Benefit 52

AWS Big Data

AUGUST 16, 2023

Conclusion In this post, we introduced a serverless CDC solution for semi-structured data using DynamoDB Streams and processing them in Iceberg tables. We demonstrated how to ingest semi-structured data in DynamoDB, identify changed data using DynamoDB Streams, and process them in Iceberg tables.

Data Lake 68

Data Lake Metadata Testing Snapshot 68

Sisense

JUNE 5, 2019

We live in an era of Big Data. The sheer volume of data currently existing is huge enough without also grappling with the amount of new information that’s generated every day. Outdated technology simply can’t keep up. Outdated technology simply can’t keep up. to store, access, and analyze their data.

Big Data 75

Big Data Cost-Benefit IoT Structured Data 75

Cloudera

JANUARY 11, 2018

I often meet with our customers to help them understand how to connect modern technology to business success. For them, they may understand that they need a data-driven strategy or the culture may aim to take a shift to being guided by data. The ever-present question at these encounters is “Where do I start?”

Strategy 40

Strategy Data Warehouse Cost-Benefit Marketing 40

Cloudera

OCTOBER 3, 2018

In 2008, I co-founded Cloudera with folks from Google, Facebook, and Yahoo to deliver a big data platform built on Hadoop to the enterprise market. We believed then, and we still believe today, that the rest of the world would need to capture, store, manage and analyze data at massive scale.

Uncertainty 75

Uncertainty IoT Risk Reporting 75

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