AWS Big Data

OCTOBER 14, 2024

Enterprise data is brought into data lakes and data warehouses to carry out analytical, reporting, and data science use cases using AWS analytical services like Amazon Athena , Amazon Redshift , Amazon EMR , and so on.

Metadata 105

Metadata Data Lake Modeling Data Warehouse 105

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 26, 2025

Analytics remained one of the key focus areas this year, with significant updates and innovations aimed at helping businesses harness their data more efficiently and accelerate insights. From enhancing data lakes to empowering AI-driven analytics, AWS unveiled new tools and services that are set to shape the future of data and analytics.

Analytics 62

Analytics Data Lake Metadata Data Warehouse 62

AWS Big Data

JANUARY 12, 2024

Ingestion: Data lake batch, micro-batch, and streaming Many organizations land their source data into their data lake in various ways, including batch, micro-batch, and streaming jobs. Amazon AppFlow can be used to transfer data from different SaaS applications to a data lake.

Data Lake 119

Data Lake Cost-Benefit Visualization Structured Data 119

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

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 Data Warehouse 52

CIO Business Intelligence

OCTOBER 2, 2024

Collect, filter, and categorize data The first is a series of processes — collecting, filtering, and categorizing data — that may take several months for KM or RAG models. Structured data is relatively easy, but the unstructured data, while much more difficult to categorize, is the most valuable.

Management 141

Management Data Governance Cost-Benefit Structured Data 141

AWS Big Data

MAY 30, 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. Solution overview Amazon Redshift is an industry-leading cloud data warehouse. The following diagram illustrates this workflow.

Data Warehouse 115

Data Warehouse Data Lake Cost-Benefit Structured Data 115

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 111

Data Lake Big Data Data Warehouse Consulting 111

AWS Big Data

DECEMBER 21, 2023

The data products used inside the company include insights from user journeys, operational reports, and marketing campaign results, among others. The data platform serves on average 60 thousand queries per day. The data volume is in double-digit TBs with steady growth as business and data sources evolve.

Data Lake 115

Data Lake Data Warehouse Data-driven B2B 115

AWS Big Data

JANUARY 6, 2025

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. Create a report on Google Analytics. Refer to API Dimensions & Metrics for details.

Analytics 98

Analytics Data Warehouse Big Data Metrics 98

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. Additionally, data is extracted from vendor APIs that includes data related to product, marketing, and customer experience.

Data Warehouse 111

Data Warehouse Analytics Data Lake Data Science 111

Cloudera

DECEMBER 11, 2020

Without meeting GxP compliance, the Merck KGaA team could not run the enterprise data lake needed to store, curate, or process the data required to inform business decisions. It established a data governance framework within its enterprise data lake. Driving innovation with secure and governed data .

Data Lake 98

Data Lake Cost-Benefit Unstructured Data Data Governance 98

AWS Big Data

FEBRUARY 7, 2023

Business needs often drive table structure, such as schema evolution (the addition of new columns, removal of existing columns, update of column names, and so on) for some of these tables in one business function that requires other business functions to replicate the same. You don’t alter queries separately in the data lake.

Data Lake 98

Data Lake Testing Big Data Structured Data 98

IBM Big Data Hub

APRIL 24, 2023

Why data warehousing is critical to a company’s success Data warehousing is the secure electronic information storage by a company or organization. It creates a trove of historical data that can be retrieved, analyzed, and reported to provide insight or predictive analysis into an organization’s performance and operations.

Data Warehouse 88

Data Warehouse Data Lake Cost-Benefit Big Data 88

AWS Big Data

AUGUST 5, 2024

These business units have varying landscapes, where a data lake is managed by Amazon Simple Storage Service (Amazon S3) and analytics workloads are run on Amazon Redshift , 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.

Data Lake 105

Data Lake Finance Sales Management 105

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 97

Analytics Data Warehouse Data Lake Metadata 97

AWS Big Data

JUNE 21, 2023

The challenge comes when we need to ask more complex questions of our data, for example, what was the year-on-year quarterly sales growth by product broken down by country? The case for a data warehouse A data warehouse is ideally suited to answer OLAP queries. To house our data, we need to define a data model.

Data Warehouse 105

Data Warehouse Data Lake OLAP Cost-Benefit 105

AWS Big Data

MAY 28, 2024

Solution overview Our solution demonstrates how financial analysts can use generative artificial intelligence (AI) to adapt their investment recommendations based on financial reports and earnings transcripts with RAG to use LLMs to generate factual content. This is unstructured data augmentation to the LLM.

Unstructured Data 119

Unstructured Data Data Warehouse Structured Data Testing 119

Jet Global

OCTOBER 30, 2020

For leaders in the finance and accounting department, it can often be frustrating to have conversations with IT experts about your reporting needs. Reporting: A Few Technical Basics. Financial and operational reports retrieve master data and transactional information from your ERP databases using something called “SQL.”

Data Lake 52

Data Lake Unstructured Data Reporting Finance 52

AWS Big Data

NOVEMBER 9, 2023

Flat files – Other systems supply data in the form of flat files of different formats. These files, stored in an SFTP location, might contain records, reports, logs, or other kinds of raw data that can be further processed and analyzed. AWS Glue – AWS Glue is used to load files into Amazon Redshift through the S3 data lake.

Data Warehouse 126

Data Warehouse Testing Data Quality Reporting 126

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 133

Enterprise Manufacturing Risk Data-driven 133

AWS Big Data

MARCH 26, 2024

Without C360, businesses face missed opportunities, inaccurate reports, and disjointed customer experiences, leading to customer churn. Pillar 3: Analytics The analytics pillar defines capabilities that help you generate insights on top of your customer data. Organizations using C360 achieved 43.9% faster time to market, and 19.1%

Data Strategy 103

Data Strategy Strategy Data Warehouse Prescriptive Analytics 103

AWS Big Data

APRIL 19, 2023

Every day, customers are challenged with how to manage their growing data volumes and operational costs to unlock the value of data for timely insights and innovation, while maintaining consistent performance. As data workloads grow, costs to scale and manage data usage with the right governance typically increase as well.

Data Warehouse 59

Data Warehouse Data Lake Unstructured Data Optimization 59

Sisense

JUNE 30, 2020

The data drawn from power visualizations comes from a variety of sources: Structured data , in the form of relational databases such as Excel, or unstructured data, deriving from text, video, audio, photos, the internet and smart devices. Visual analytics and data visualizations in action.

Visualization 93

Visualization Analytics Dashboards Data-driven 93

AWS Big Data

OCTOBER 2, 2023

JSON data in Amazon Redshift Amazon Redshift enables storage, processing, and analytics on JSON data through the SUPER data type, PartiQL language, materialized views, and data lake queries. The function JSON_PARSE allows you to extract the binary data in the stream and convert it into the SUPER data type.

Cost-Benefit 115

Cost-Benefit Metadata Structured Data Data-driven 115

Cloudera

JULY 26, 2021

Auditabily: Data security and compliance constituents need to understand how data changes, where it originates from and how data consumers interact with it. a technology choice such as Spark Streaming is overly focused on throughput at the expense of latency) or data formats (e.g., data warehousing).

Strategy 119

Strategy Data Science Unstructured Data Marketing 119

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

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! Enriching (e.g.,

Modeling 84

Modeling Big Data IoT Data Warehouse 84

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

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

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. Getting started with AWS SCT is a straightforward process. Also, consider following the best practices for AWS SCT.

Testing 111

Testing Data Warehouse Metrics Cost-Benefit 111

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

Cloudera

OCTOBER 7, 2021

Those decentralization efforts appeared under different monikers through time, e.g., data marts versus data warehousing implementations (a popular architectural debate in the era of structured data) then enterprise-wide data lakes versus smaller, typically BU-Specific, “data ponds”.

Metadata 124

Metadata Cost-Benefit Enterprise Interactive 124

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 98

Data Lake Data Warehouse Sales Data-driven 98

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 98

Big Data Consulting Software Unstructured Data 98

AWS Big Data

JUNE 6, 2023

Unless, of course, the rest of their data also resides in the Google Cloud. In this post we showcase how we used AWS Glue to move siloed digital analytics data, with inconsistent arrival times, to AWS S3 (our Data Lake) and our central data warehouse (DWH), Snowflake. It consists of full-day and intraday tables.

Analytics 59

Analytics Data Lake Testing Optimization 59