AWS Big Data

JANUARY 8, 2024

It aims to provide a framework to create low-latency streaming applications on the AWS Cloud using Amazon Kinesis Data Streams and AWS purpose-built data analytics services. In this post, we will review the common architectural patterns of two use cases: Time Series Data Analysis and Event Driven Microservices.

Analytics 115

Analytics IoT Data-driven Snapshot 115

AWS Big Data

NOVEMBER 16, 2023

Amazon Redshift is a popular cloud data warehouse, offering a fully managed cloud-based service that seamlessly integrates with an organization’s Amazon Simple Storage Service (Amazon S3) data lake, real-time streams, machine learning (ML) workflows, transactional workflows, and much more—all while providing up to 7.9x

Enterprise 86

Enterprise Data Warehouse Snapshot Cost-Benefit 86

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 86

Data Science Data Analytics Prescriptive Analytics Analytics 86

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

CIO Business Intelligence

JUNE 29, 2022

Azure Data Factory. Azure Data Explorer is used to store and query data in services such as Microsoft Purview, Microsoft Defender for Endpoint, Microsoft Sentinel, and Log Analytics in Azure Monitor. Azure Data Lake Analytics.

Data Lake 116

Data Lake Analytics Data Warehouse Machine Learning 116

AWS Big Data

MAY 16, 2024

In our increasingly interconnected world, where every step we take, every location we visit, and every event we encounter leaves a digital footprint, the volume and complexity of geospatial data are expanding at an astonishing pace. This often overwhelms traditional visualization tools and methods. But what makes them special?

Data Warehouse 82

Data Warehouse Visualization Cost-Benefit Optimization 82

AWS Big Data

APRIL 20, 2023

In a modern data architecture, unified analytics enable you to access the data you need, whether it’s stored in a data lake or a data warehouse. Select the Visual with a blank canvas , because we’re authoring a job from scratch, then choose Create.

Visualization 79

Visualization Data Warehouse Big Data Data Lake 79

Peter James Thomas

APRIL 3, 2020

Busy Executives and Managers have their information needs best served via visual exhibits that are focussed on their areas of priority and highlight things that are of specific concern to them. In fact is is the crucial final link between an organisation’s data and the people who need to use it.

Dashboards 61

Dashboards Reporting Sales Data Lake 61

Alation

FEBRUARY 13, 2020

Data Literacy—Many line-of-business people have responsibilities that depend on data analysis but have not been trained to work with data. Their tendency is to do just enough data work to get by, and to do that work primarily in Excel spreadsheets. People – Which data stakeholders will you bring on board at what times?

Metadata 52

Metadata Data Governance Cost-Benefit Visualization 52

AWS Big Data

MARCH 26, 2024

You can subscribe to data products that help enrich customer profiles, for example demographics data, advertising data, and financial markets data. Amazon Kinesis ingests streaming events in real time from point-of-sales systems, clickstream data from mobile apps and websites, and social media data.

Data Strategy 70

Data Strategy Strategy Data Warehouse Prescriptive Analytics 70

AWS Big Data

NOVEMBER 29, 2023

With Amazon Bedrock , you can privately customize FMs for your specific use case using a small set of your own labeled data through a visual interface without writing any code. You also need services to store data for analysis and machine learning (ML) like Amazon Simple Storage Service (Amazon S3).

Data Warehouse 111

Data Warehouse Data Lake Data Integration Dashboards 111

Cloudera

JANUARY 21, 2021

While cloud-native, point-solution data warehouse services may serve your immediate business needs, there are dangers to the corporation as a whole when you do your own IT this way. Cloudera Data Warehouse (CDW) is here to save the day! CDW is an integrated data warehouse service within Cloudera Data Platform (CDP).

Data Lake 93

Data Lake Data Warehouse IT Analytics 93

AWS Big Data

FEBRUARY 1, 2023

With data volumes exhibiting a double-digit percentage growth rate year on year and the COVID pandemic disrupting global logistics in 2021, it became more critical to scale and generate near-real-time data. You can visually create, run, and monitor extract, transform, and load (ETL) pipelines to load data into your data lakes.

Optimization 52

Optimization Forecasting Data Lake Metadata 52

AWS Big Data

JULY 19, 2023

Amazon Redshift is a fully managed and petabyte-scale cloud data warehouse that is used by tens of thousands of customers to process exabytes of data every day to power their analytics workload. You can structure your data, measure business processes, and get valuable insights quickly can be done by using a dimensional model.

Modeling 69

Modeling Sales Data Warehouse Snapshot 69

AWS Big Data

JULY 25, 2023

It automatically provisions and intelligently scales data warehouse compute capacity to deliver fast performance, and you pay only for what you use. Just load your data and start querying right away in the Amazon Redshift Query Editor or in your favorite business intelligence (BI) tool. Ashish Agrawal is a Sr.

Metrics 81

Metrics Data Warehouse Dashboards Snapshot 81

Domino Data Lab

APRIL 3, 2019

Most of the data management moved to back-end servers, e.g., databases. So we had three tiers providing a separation of concerns: presentation, logic, data. Note that data warehouse (DW) and business intelligence (BI) practices both emerged circa 1990. in lieu of simply landing in a data lake.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

Cloudera

DECEMBER 12, 2018

After having rebuilt their data warehouse, I decided to take a little bit more of a pointed role, and I joined Oracle as a database performance engineer. I spent eight years in the real-world performance group where I specialized in high visibility and high impact data warehousing competes and benchmarks.

Data Warehouse 42

Data Warehouse Marketing Big Data Data Lake 42

AWS Big Data

NOVEMBER 14, 2023

However, in many organizations, data is typically spread across a number of different systems such as software as a service (SaaS) applications, operational databases, and data warehouses. Such data silos make it difficult to get unified views of the data in an organization and act in real time to derive the most value.

IoT 56

IoT Data-driven Data Lake Data Strategy 56

AWS Big Data

JUNE 29, 2023

Notebooks are provisioned quickly and provide a way for you to instantly view and analyze your streaming data. This pipeline could further be used to send data to Amazon OpenSearch Service or other targets for additional processing and visualization.

Data Analytics 75

Data Analytics Analytics IoT Data Lake 75

Sisense

JANUARY 15, 2021

Big data is now modeled and queried using advanced coding languages like SQL, Python, and R. And rather than answering prescriptive questions — something that BI teams excel at — data teams are able to model future events and understand how changing a past variable could have affected the present.

Analytics 75

Analytics Data-driven Business Intelligence Visualization 75

Cloudera

OCTOBER 25, 2022

Cloud data lakehouses provide significant scaling, agility, and cost advantages compared to cloud data lakes and cloud data warehouses. They combine the best of both worlds: flexibility, cost effectiveness of data lakes and performance, and reliability of data warehouses.”.

Data Processing 52

Data Processing Data Lake Cost-Benefit Risk 52

AWS Big Data

JUNE 6, 2023

You can use AWS Glue to create, run, and monitor data integration and ETL (extract, transform, and load) pipelines and catalog your assets across multiple data stores. Hundreds of thousands of customers use data lakes for analytics and ML to make data-driven business decisions.

Data Quality 76

Data Quality Data Lake Data-driven Metrics 76

AWS Big Data

MARCH 3, 2023

Additionally, the scale is significant because the multi-tenant data sources provide a continuous stream of testing activity, and our users require quick data refreshes as well as historical context for up to a decade due to compliance and regulatory demands. Finally, data integrity is of paramount importance.

Software 52

Software Data Lake Testing Cost-Benefit 52

Cloudera

MAY 16, 2018

This approach also relates to monitoring internal fiduciary risk by tying separate events together, such as a large position (relative to historic norms) being taken immediately after the risk model that would have flagged it was modified in a separate system. However, in this case, that output is ingested into a data lake.

Data Lake 42

Data Lake Risk Visualization Unstructured Data 42

Alation

APRIL 14, 2022

A useful feature for exposing patterns in the data. Visual Profiling. Supports the ability to interact with the actual data and perform analysis on it. This provides the facility a time or event for a job to run and offers useful post-run information. Automatic sampling to test transformation. Scheduling. Target Matching.

Metadata 59

Metadata Data Governance Modeling Data-driven 59

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 81

Data Warehouse Data Lake OLAP Cost-Benefit 81

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

Sisense

JULY 6, 2021

To drive this point home, Yonatan Dolan, an Analytics Specialist from AWS, introduced AWS’ new Lake House architecture. This cutting-edge service integrates the abilities of a data lake, a data warehouse, and purpose-built stores, to enable unified governance and easy data movement.

Data Lake 52

Data Lake Data Warehouse Data-driven Unstructured Data 52

AWS Big Data

AUGUST 1, 2023

Although Jira Cloud provides reporting capability, loading this data into a data lake will facilitate enrichment with other business data, as well as support the use of business intelligence (BI) tools and artificial intelligence (AI) and machine learning (ML) applications. Search for the Jira Cloud connector.

Data Lake 86

Data Lake Data Transformation Cost-Benefit Data-driven 86

AWS Big Data

DECEMBER 21, 2023

To speed up the self-service analytics and foster innovation based on data, a solution was needed to provide ways to allow any team to create data products on their own in a decentralized manner. To create and manage the data products, smava uses Amazon Redshift , a cloud data warehouse.

Data Lake 92

Data Lake Data Warehouse Data-driven B2B 92

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

Jet Global

FEBRUARY 23, 2024

Why Data Mapping is Important Data mapping is a critical element of any data management initiative, such as data integration, data migration, data transformation, data warehousing, or automation. Data mapping helps standardize, visualize, and understand data across different systems and applications.

Data Warehouse 52

Data Warehouse Reporting Data Transformation Sales 52

Jet Global

APRIL 26, 2022

Jet Reports now offers high performance connectivity with options to connect to Synapse/Azure Data Lakes, BYOD, SQL or your Cubes and Tabular models. Create accurate charts, graphs, and other visuals that combine the most current data from multiple applications in just a few clicks. With the release of Jet Reports 22.1,

Reporting 52

Reporting Finance Cost-Benefit Forecasting 52