AWS Big Data

JANUARY 8, 2024

This is the first post to a blog series that offers common architectural patterns in building real-time data streaming infrastructures using Kinesis Data Streams for a wide range of use cases. 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

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 109

Data Lake Unstructured Data Data Warehouse Data Quality 109

CIO Business Intelligence

OCTOBER 13, 2023

Information/data governance architect: These individuals establish and enforce data governance policies and procedures. Analytics/data science architect: These data architects design and implement data architecture supporting advanced analytics and data science applications, including machine learning and artificial intelligence.

Data Architecture 131

Data Architecture Data Warehouse Statistics Visualization 131

erwin

JUNE 26, 2020

Organizations with particularly deep data stores might need a data catalog with advanced capabilities, such as automated metadata harvesting to speed up the data preparation process. Three Types of Metadata in a Data Catalog. Technical Metadata. Operational Metadata.

Metadata 132

Metadata Cost-Benefit Measurement Data-driven 132

AWS Big Data

JUNE 9, 2023

A modern data architecture enables companies to ingest virtually any type of data through automated pipelines into a data lake, which provides highly durable and cost-effective object storage at petabyte or exabyte scale.

Data Lake 115

Data Lake Metadata Optimization Statistics 115

CIO Business Intelligence

JUNE 14, 2023

When adding more storage nodes, it is important to ensure that the capacity addition is more optimal and efficient. This can be achieved by utilizing dense storage nodes and implementing fault tolerance and resiliency measures for managing such a large amount of data. Evaluate data across the full lifecycle.

Unstructured Data 63

Unstructured Data IT Manufacturing Visualization 63

IBM Big Data Hub

JANUARY 17, 2023

However, most of their raw data remains unused and trapped in data silos, making extracting insights difficult. The rise of cloud object storage has driven the cost of storage down and new technologies have evolved to access and query the data stored in there more efficiently.

Data Lake 52

Data Lake Metadata Data Warehouse Data Governance 52

Cloudera

SEPTEMBER 15, 2022

Apache Ozone is a distributed, scalable, and high-performance object store , available with Cloudera Data Platform (CDP), that can scale to billions of objects of varying sizes. Structured data (such as name, date, ID, and so on) will be stored in regular SQL databases like Hive or Impala databases. Diversity of workloads.

Metadata 87

Metadata Big Data Optimization Unstructured Data 87

AWS Big Data

MARCH 2, 2023

Apache Iceberg is an open table format for very large analytic datasets, which captures metadata information on the state of datasets as they evolve and change over time. Iceberg has become very popular for its support for ACID transactions in data lakes and features like schema and partition evolution, time travel, and rollback.

Data Lake 120

Data Lake Data Processing Metadata Snapshot 120

Cloudera

SEPTEMBER 9, 2022

Imagine quickly answering burning business questions nearly instantly, without waiting for data to be found, shared, and ingested. Imagine independently discovering rich new business insights from both structured and unstructured data working together, without having to beg for data sets to be made available.

Metadata 100

Metadata Machine Learning Unstructured Data Data Lake 100

Sisense

AUGUST 21, 2020

AI and machine learning are the future of every industry, especially data and analytics. Reading through the Gartner Top 10 Trends in Data and Analytics for 2020 , I was struck by how different terms mean different things to different audiences under different contexts. Trend 1: Smarter, faster, more responsible AI.

Analytics 112

Analytics Machine Learning Dashboards Visualization 112

erwin

JUNE 27, 2019

The need for an effective data modeling tool is more significant than ever. For decades, data modeling has provided the optimal way to design and deploy new relational databases with high-quality data sources and support application development.

Measurement 81

Measurement Modeling Unstructured Data Metadata 81

Ontotext

DECEMBER 1, 2023

Atanas Kiryakov presenting at KGF 2023 about Where Shall and Enterprise Start their Knowledge Graph Journey Only data integration through semantic metadata can drive business efficiency as “it’s the glue that turns knowledge graphs into hubs of metadata and content”.

Metadata 78

Metadata Sales Consulting Enterprise 78

IBM Big Data Hub

DECEMBER 16, 2022

An enterprise data catalog does all that a library inventory system does – namely streamlining data discovery and access across data sources – and a lot more. For example, data catalogs have evolved to deliver governance capabilities like managing data quality and data privacy and compliance.

Metadata 52

Metadata Data Quality Data-driven Data Governance 52

Smart Data Collective

APRIL 5, 2022

IBM Watson Studio is a very popular solution for handling machine learning and data science tasks. Companies working on AI technology can use it to improve scalability and optimize the decision-making process. This feature helps automate many parts of the data preparation and data model development process. Neptune.ai.

Cost-Benefit 123

Cost-Benefit Machine Learning Data Science Unstructured Data 123

Octopai

FEBRUARY 8, 2020

Although it was only one of many Mars mission failures in the history of space travel, it was one that easily could have been prevented by achieving the optimal set of equipment and communication to power space travel. . Moreover, others need to trace data history, get its context to resolve an issue before it actually becomes an issue.

Metadata 63

Metadata Key Performance Indicator Unstructured Data Business Intelligence 63

IBM Big Data Hub

FEBRUARY 14, 2024

The IBM team is even using generative AI to create synthetic data to build more robust and trustworthy AI models and to stand in for real-world data protected by privacy and copyright laws. These systems can evaluate vast amounts of data to uncover trends and patterns, and to make decisions.

Cost-Benefit 86

Cost-Benefit Insurance Unstructured Data Machine Learning 86

FineReport

FEBRUARY 5, 2020

Based on the study of the evaluation criteria of Gartner Magic Quadrant for analytics and Business Intelligence Platforms, I have summarized top 10 key features of BI tools for your reference. Overall, as users’ data sources become more extensive, their preferences for BI are changing. Metadata management. Analytics dashboards.

Metadata 98

Metadata Dashboards Informatics Visualization 98

Cloudera

OCTOBER 7, 2021

Application Logic: Application logic refers to the type of data processing, and can be anything from analytical or operational systems to data pipelines that ingest data inputs, apply transformations based on some business logic and produce data outputs.

Metadata 124

Metadata Cost-Benefit Enterprise Interactive 124

CIO Business Intelligence

MARCH 6, 2023

Advancements in analytics and AI as well as support for unstructured data in centralized data lakes are key benefits of doing business in the cloud, and Shutterstock is capitalizing on its cloud foundation, creating new revenue streams and business models using the cloud and data lakes as key components of its innovation platform.

Data Lake 65

Data Lake Cost-Benefit Recreation/Entertainment Experimentation 65

Domino Data Lab

JULY 2, 2019

In other words, using metadata about data science work to generate code. In this case, code gets generated for data preparation, where so much of the “time and labor” in data science work is concentrated. Clearly, SQL helps reduce cognitive load for those who are learning about data management and analytics.

Metadata 105

Metadata Machine Learning Data Science Data-driven 105

IBM Big Data Hub

JANUARY 5, 2023

Monitor and identify data quality issues closer to the source to mitigate the potential impact on downstream processes or workloads. Efficiently adopt data platforms and new technologies for effective data management. Apply metadata to contextualize existing and new data to make it searchable and discoverable.

Data Quality 52

Data Quality Data Architecture Strategy Data Lake 52

AWS Big Data

FEBRUARY 22, 2023

The data lake implemented by Ruparupa uses Amazon S3 as the storage platform, AWS Database Migration Service (AWS DMS) as the ingestion tool, AWS Glue as the ETL (extract, transform, and load) tool, and QuickSight for analytic dashboards. Data had to be manually processed by data analysts, and data mining took a long time.

Data Lake 52

Data Lake Dashboards Cost-Benefit Metadata 52

AWS Big Data

MARCH 25, 2024

Streaming jobs constantly ingest new data to synchronize across systems and can perform enrichment, transformations, joins, and aggregations across windows of time more efficiently. For building such a data store, an unstructured data store would be best. This use case fits very well in the streaming analytics domain.

Data Lake 92

Data Lake Unstructured Data Management Modeling 92

Cloudera

SEPTEMBER 17, 2020

They were not able to quickly and easily query and analyze huge amounts of data as required. They also needed to combine text or other unstructured data with structured data and visualize the results in the same dashboards. Events or time-series data served by our real-time events or time-series data store solutions.

Experimentation 81

Experimentation Data Warehouse Dashboards Visualization 81

Ontotext

NOVEMBER 22, 2020

Businesses wanted a way to make pie and not an in-depth understanding of forward-chaining, inferential explosion or SPARQL optimizations. Ontotext is also on the list of vendors supporting knowledge graph capabilities in their “2021 Planning Guide for Data Analytics and Artificial Intelligence” report.

Metadata 72

Metadata Cost-Benefit Unstructured Data Technology 72

Alation

JUNE 2, 2022

In part two of this series, I’ll dive more deeply into AI/ML and data lineage, in the cloud and otherwise, and discuss how data governance and security can support these critical use cases, wherever they reside. Data management is not yet a solved problem, but modern data management is leagues ahead of prior approaches.

Modeling 52

Modeling Data Governance Statistics Unstructured Data 52

Cloudera

NOVEMBER 22, 2021

In legacy analytical systems such as enterprise data warehouses, the scalability challenges of a system were primarily associated with computational scalability, i.e., the ability of a data platform to handle larger volumes of data in an agile and cost-efficient way. Introduction. CRM platforms).

Data Processing 92

Data Processing Data Warehouse Enterprise Visualization 92

AWS Big Data

MARCH 10, 2023

Since the deluge of big data over a decade ago, many organizations have learned to build applications to process and analyze petabytes of data. Data lakes have served as a central repository to store structured and unstructured data at any scale and in various formats.

Data Lake 105

Data Lake Sales Data Warehouse Snapshot 105

Cloudera

SEPTEMBER 1, 2020

It is designed to simplify deployment, configuration, and serviceability of Solr-based analytics applications. DDE also makes it much easier for application developers or data workers to self-service and get started with building insight applications or exploration services based on text or other unstructured data (i.e.

Snapshot 68

Snapshot Unstructured Data Dashboards Interactive 68

Rita Sallam

JULY 22, 2016

And here we are now, past the tipping point of a more than 10 to 11 year transition away from IT-centric reporting platforms to modern BI and analytics platforms that make up much of the new buying in the BI and Analytics market. A modern BI platform supports IT-enabled analytic content development. Moving to Modern.

Analytics 40

Analytics Business Intelligence Metadata Statistics 40

Sisense

MAY 28, 2020

In the Clouds is where we explore the ways cloud-native architecture, cloud data storage, and cloud analytics are changing key industries and business practices, with anecdotes from experts, how-to’s, and more to help your company excel in the cloud era. The world of data is constantly changing and speeding up every day.

Internet of Things 83

Internet of Things Metadata Data-driven Unstructured Data 83

AWS Big Data

FEBRUARY 21, 2023

We dive deep into a hybrid approach that aims to circumvent the issues posed by these two and also provide recommendations to take advantage of this approach for healthcare data warehouses using Amazon Redshift. What is a dimensional data model? It optimizes the database for faster data retrieval. What is a data vault?

Data Warehouse 67

Data Warehouse Data Lake Cost-Benefit Modeling 67

Cloudera

AUGUST 30, 2018

How do I get to the next level in the data-driven journey fast enough? How do I meet a growing demand for self-serve BI, while not exploding my data warehouse budgets? How can I optimize my rate of return and continue to drive innovation? Tough decisions. Complex scenarios. can deliver that technology foundation. .

Enterprise 40

Enterprise Data-driven Digital Transformation Machine Learning 40

Cloudera

AUGUST 21, 2020

And next to those legacy ERP, HCM, SCM and CRM systems, that mysterious elephant in the room – that “Big Data” platform running in the data center that is driving much of the company’s analytics and BI – looks like a great potential candidate. . Streaming data analytics. . There it is.

Cost-Benefit 74

Cost-Benefit Big Data ROI Risk 74

Ontotext

SEPTEMBER 2, 2020

Instead, it creates a unified way, sometimes called a data fabric, of accessing an organization’s data as well as 3rd party or global data in a seamless manner. Data is represented in a holistic, human-friendly and meaningful way. Knowledges Graphs for Memory Recall. It’s semantics and it’s knowledge graphs.

Insurance 72

Insurance Metadata Publishing Unstructured Data 72

Laminar Security

MAY 3, 2023

They define DSPM technologies this way: “DSPM technologies can discover unknown data and categorize structured and unstructured data across cloud service platforms. This accessibility of data is vital to business growth, but has also resulted in a significant increase in risk.

Management 52

Management Risk Risk Management Data Processing 52