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 68

Data Strategy Strategy Data Warehouse Prescriptive Analytics 68

Cloudera

SEPTEMBER 15, 2021

And that comes down to being able to act on data at the precise time it requires action. Deploying machine learning (ML) and analytics capabilities at the edge is what makes this possible. . In such a scenario, data latency is essentially unavoidable — and, when real-time action is required, inadmissible.

IoT 120

IoT Analytics Internet of Things Data Lake 120

CIO Business Intelligence

APRIL 29, 2022

Software development, once solely the domain of human programmers, is now increasingly the by-product of data being carefully selected, ingested, and analysed by machine learning (ML) systems in a recurrent cycle. The shift away from ‘Software 1.0’ era is upon us.

Data Governance 142

Data Governance IT Risk Data Lake 142

Cloudera

JANUARY 21, 2021

Storing data in a proprietary, single-workload solution also recreates dangerous data silos all over again, as it locks out other types of workloads over the same shared data. The Data Lake service in Cloudera’s Data Platform provides a central place to understand, manage, secure, and govern data assets across the enterprise.

Data Lake 94

Data Lake Data Warehouse IT Analytics 94

CIO Business Intelligence

SEPTEMBER 8, 2022

Most organizations understand the profound impact that data is having on modern business. In Foundry’s 2022 Data & Analytics Study , 88% of IT decision-makers agree that data collection and analysis have the potential to fundamentally change their business models over the next three years.

Cost-Benefit 105

Cost-Benefit Internet of Things Data-driven Data Lake 105

Alation

FEBRUARY 13, 2020

Today, we’re announcing that Alation has closed a $50 million Series C funding led by Sapphire Ventures, with participation from new investor Salesforce Ventures and our existing investors Costanoa Ventures, DCVC (Data Collective), Harmony Partners and Icon Ventures. And, the data catalog market has had a year of incredible growth.

Enterprise 52

Enterprise Data Lake Machine Learning Data-driven 52

CIO Business Intelligence

JULY 12, 2023

AI improves diaper manufacturing “All areas of P&G’s business are being impacted by emerging technologies like automation, AI, and machine learning,” says Vittorio Cretella, CIO of Procter & Gamble. P&G engineers developed a high-speed data collection system to capture data to use for training AI models.

Manufacturing 91

Manufacturing Cost-Benefit Data Lake Optimization 91

FineReport

MARCH 24, 2024

Data Analyst Job Description: Major Tasks and Duties Data analysts collaborate with management to prioritize information needs, collect and interpret business-critical data, and report findings. Certified Analytics Professional (CAP) , providing advanced insights into converting data into actionable insights.

Statistics 52

Statistics Data mining Visualization Reporting 52

Cloudera

JANUARY 24, 2022

Working with Cloudera, Keck created a data lake that eliminated manual data collection errors and gave visibility organization-wide. Winner of the Data Impact Awards 2021: Data for Good. You can become a data hero too.

Data Lake 65

Data Lake Risk Machine Learning Data Collection 65

Alation

FEBRUARY 13, 2020

Figure 1 illustrates the typical metadata subjects contained in a data catalog. Figure 1 – Data Catalog Metadata Subjects. Datasets are the files and tables that data workers need to find and access. They may reside in a data lake, warehouse, master data repository, or any other shared data resource.

Metadata 64

Metadata Data Lake Recreation/Entertainment Big Data 64

bridgei2i

MARCH 11, 2021

The key to taking advantage of AI tools for small businesses is data. Easily understandable, highly curated, and reliable data helps Machine Learning (ML) tools evolve. As long as small businesses don’t have efficient data governance strategies, they can’t properly use AI and ML-powered tools. in the system.

Key Performance Indicator 52

Key Performance Indicator Data Governance Data Lake Metadata 52

Cloudera

SEPTEMBER 8, 2021

Putting aside operational efficiency for a moment, let us now consider the constraint “accelerated time frames” If data flows, ETL pipelines, BI reports and machine learning pipelines all need to be rewritten or heavily modified, this can significantly extend the time to value and increase the risk of moving to the cloud.

Data Lake 79

Data Lake Enterprise Data-driven Data Strategy 79

Darkhorse

JULY 6, 2017

So what is data wrangling? Let’s imagine the process of building a data lake. Let’s further pretend you’re starting out with the aim of doing a big predictive modeling thing using machine learning. First off, data wrangling is gathering the appropriate data. I hope you enjoy that sort of thing.

Data Lake 74

Data Lake Sales Machine Learning Visualization 74

Alation

JANUARY 26, 2023

That’s why many organizations invest in technology to improve data processes, such as a machine learning data pipeline. However, data needs to be easily accessible, usable, and secure to be useful — yet the opposite is too often the case. This is “table stakes” for any data governance program!).

Data Governance 52

Data Governance Strategy Data Quality Marketing 52

Cloudera

NOVEMBER 22, 2021

In addition, data pipelines include more and more stages, thus making it difficult for data engineers to compile, manage, and troubleshoot those analytical workloads. In addition, data pipelines include more and more stages, thus making it difficult for data engineers to compile, manage, and troubleshoot those analytical workloads.

Data Processing 94

Data Processing Data Warehouse Enterprise Visualization 94

datapine

AUGUST 29, 2022

James Warren, on the other part, is a successful analytics architect with a background in machine learning and scientific computing. 5) Data Analytics Made Accessible, by Dr. Anil Maheshwari. Best for : the new intern who has no idea what data science even means.

Big Data 263

Big Data Data Analytics Analytics Data mining 263

BizAcuity

MARCH 1, 2019

This is where AI-based analysis and response play a critical role in extracting optimal value from the data. When we say AI, we really mean machine learning because ML provides the ability to detect patterns in data presented. At the backend, based on the data collected, data is stored in data lakes.

IoT 56

IoT Internet of Things Big Data Data-driven 56

Alation

FEBRUARY 20, 2020

More than any other advancement in analytic systems over the last 10 years, Hadoop has disrupted data ecosystems. By dramatically lowering the cost of storing data for analysis, it ushered in an era of massive data collection. You did not have to understand or prepare the data to get it into Hadoop, so people rarely did.

Data Lake 52

Data Lake Metadata Structured Data Big Data 52

Sisense

APRIL 26, 2020

In our modern digital world, proper use of data can play a huge role in a business’s success. Datasets are exploding at an ever-accelerating rate, so collecting and analyzing data to maximum effect is crucial. Companies and businesses focus a lot on data collection in order to make sure they can get valuable insights out of it.

Unstructured Data 52

Unstructured Data Data Warehouse Structured Data Data mining 52

CIO Business Intelligence

MAY 26, 2022

When companies first start deploying artificial intelligence and building machine learning projects, the focus tends to be on theory. But the tools that data scientists use to create these proofs of concept often don’t translate well into production systems. Is there a model that can provide the necessary results?

Machine Learning 138

Machine Learning Modeling Data-driven Dashboards 138

Alation

MAY 16, 2023

Data Integration A data pipeline can be used to gather data from various disparate sources in one data store. This makes it easier to compare and contrast information and provides organizations with a unified view of their data. It’s worth noting that a data pipeline may have more than one data source.

Data Lake 69

Data Lake Data Governance Data Warehouse Data Processing 69

CIO Business Intelligence

MAY 28, 2022

When companies first start deploying artificial intelligence and building machine learning projects, the focus tends to be on theory. But the tools that data scientists use to create these proofs of concept often don’t translate well into production systems. Is there a model that can provide the necessary results?

Machine Learning 124

Machine Learning Modeling Data-driven Dashboards 124

Alation

MAY 16, 2023

Data Integration A data pipeline can be used to gather data from various disparate sources in one data store. This makes it easier to compare and contrast information and provides organizations with a unified view of their data. It’s worth noting that a data pipeline may have more than one data source.

Data Lake 40

Data Lake Data Governance Data Warehouse Data Processing 40

CIO Business Intelligence

JUNE 7, 2023

Like the NFL, the NBA CTO opted to partner with Microsoft to leverage its Azure cloud platform, which Bhagavathula says contained all the digital components necessary to build the association’s streaming platform, while providing a cloud data lake and machine learning models the NBA could capitalize on for next-generation applications.

Digital Transformation 52

Digital Transformation Recreation/Entertainment Machine Learning Data Lake 52

CIO Business Intelligence

NOVEMBER 28, 2023

With each game release and update, the amount of unstructured data being processed grows exponentially, Konoval says. This volume of data poses serious challenges in terms of storage and efficient processing,” he says. To address this problem RetroStyle Games invested in data lakes. Make ample use of AI.

Unstructured Data 120

Unstructured Data Data-driven Visualization Data Quality 120

Alation

FEBRUARY 13, 2020

In his book titled “The Fourth Industrial Revolution,” Klaus Schwab describes the age as, “characterized by a much more ubiquitous and mobile internet, by smaller and more powerful sensors that have become cheaper, and by artificial intelligence and machine learning.” Each of your organizations has something impossible to accomplish.

Machine Learning 52

Machine Learning Data-driven Big Data Technology 52

Alation

FEBRUARY 1, 2022

Today organizations view data as the “new oil”, an asset that, if used wisely, can support innovation while providing a meaningful competitive advantage and a better customer experience. And with data collection and replication growing so quickly, governance is more important than ever. Curious to learn more?

Data Lake 52

Data Lake Data Governance ROI Cost-Benefit 52

IBM Big Data Hub

AUGUST 4, 2023

By leveraging data services and APIs, a data fabric can also pull together data from legacy systems, data lakes, data warehouses and SQL databases, providing a holistic view into business performance. Then, it applies these insights to automate and orchestrate the data lifecycle.

Data Architecture 59

Data Architecture Data Lake Machine Learning Data Governance 59