datapine

MAY 2, 2023

Table of Contents 1) Benefits Of Big Data In Logistics 2) 10 Big Data In Logistics Use Cases Big data is revolutionizing many fields of business, and logistics analytics is no exception. The complex and ever-evolving nature of logistics makes it an essential use case for big data applications.

Big Data 275

Big Data Internet of Things Cost-Benefit Optimization 275

AWS Big Data

NOVEMBER 22, 2024

Amazon Redshift has launched a session reuse capability for the Data API that can significantly streamline multi-step, stateful workloads such as exchange, transform, and load (ETL) pipelines, reporting processes, and other flows that involve sequential queries.

Data Warehouse 105

Data Warehouse Recreation/Entertainment Cost-Benefit Data-driven 105

Wayne Yaddow

FEBRUARY 26, 2025

AI is transforming how senior data engineers and data scientists validate data transformations and conversions. Artificial intelligence-based verification approaches aid in the detection of anomalies, the enforcement of data integrity, and the optimization of pipelines for improved efficiency.

Data Transformation 52

Data Transformation Testing Data-driven Data Quality 52

Sisense

MAY 11, 2021

You can’t talk about data analytics without talking about data modeling. 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. Building the right data model is an important part of your data strategy.

Modeling 84

Modeling Big Data IoT Data Warehouse 84

Cloudera

AUGUST 17, 2021

When we announced the GA of Cloudera Data Engineering back in September of last year, a key vision we had was to simplify the automation of data transformation pipelines at scale. Typically users need to ingest data, transform it into optimal format with quality checks, and optimize querying of the data by visual analytics tool.

Management 115

Management Cost-Benefit Data Transformation Optimization 115

DataKitchen

JULY 27, 2023

Let’s go through the ten Azure data pipeline tools Azure Data Factory : This cloud-based data integration service allows you to create data-driven workflows for orchestrating and automating data movement and transformation. You can use it for big data analytics and machine learning workloads.

Machine Learning 130

Machine Learning Cost-Benefit Data Transformation Testing 130

CIO Business Intelligence

JULY 5, 2022

Business analytics is the practical application of statistical analysis and technologies on business data to identify and anticipate trends and predict business outcomes. Data analytics is used across disciplines to find trends and solve problems using data mining , data cleansing, data transformation, data modeling, and more.

Business Analytics 136

Business Analytics Prescriptive Analytics Data mining Diagnostic Analytics 136

Smart Data Collective

OCTOBER 13, 2021

There are countless examples of big data transforming many different industries. There is no disputing the fact that the collection and analysis of massive amounts of unstructured data has been a huge breakthrough. How is Data Virtualization performance optimized? In improving operational processes.

Visualization 145

Visualization Cost-Benefit Big Data Prescriptive Analytics 145

DataKitchen

DECEMBER 9, 2022

DataOps involves close collaboration between data scientists, IT professionals, and business stakeholders, and it often involves the use of automation and other technologies to streamline data-related tasks. One of the key benefits of DataOps is the ability to accelerate the development and deployment of data-driven solutions.

Machine Learning 130

Machine Learning Data-driven Optimization Data Analytics 130

AWS Big Data

NOVEMBER 15, 2023

BMW Group uses 4,500 AWS Cloud accounts across the entire organization but is faced with the challenge of reducing unnecessary costs, optimizing spend, and having a central place to monitor costs. The ultimate goal is to raise awareness of cloud efficiency and optimize cloud utilization in a cost-effective and sustainable manner.

Dashboards 111

Dashboards Analytics Metadata Data Warehouse 111

CIO Business Intelligence

JANUARY 19, 2024

The exam covers everything from fundamental to advanced data science concepts such as big data best practices, business strategies for data, building cross-organizational support, machine learning, natural language processing, scholastic modeling, and more.

Data Science 126

Data Science Machine Learning Predictive Modeling Forecasting 126

AWS Big Data

APRIL 11, 2023

Accurately predicting demand for products allows businesses to optimize inventory levels, minimize stockouts, and reduce holding costs. Solution overview In today’s highly competitive business landscape, it’s essential for retailers to optimize their inventory management processes to maximize profitability and improve customer satisfaction.

Forecasting 97

Forecasting Management IoT Data-driven 97

AWS Big Data

JULY 18, 2024

The main driving factors include lower total cost of ownership, scalability, stability, improved ingestion connectors (such as Data Prepper , Fluent Bit, and OpenSearch Ingestion), elimination of external cluster managers like Zookeeper, enhanced reporting, and rich visualizations with OpenSearch Dashboards.

Dashboards 113

Dashboards Testing Data-driven Visualization 113

datapine

SEPTEMBER 29, 2022

Business/Data Analyst: The business analyst is all about the “meat and potatoes” of the business. These needs are then quantified into data models for acquisition and delivery. This person (or group of individuals) ensures that the theory behind data quality is communicated to the development team. 2 – Data profiling.

Data Quality 241

Data Quality Metrics Data-driven Management 241

IBM Big Data Hub

OCTOBER 16, 2023

It includes processes that trace and document the origin of data, models and associated metadata and pipelines for audits. Foundation models: The power of curated datasets Foundation models , also known as “transformers,” are modern, large-scale AI models trained on large amounts of raw, unlabeled data.

Risk 70

Risk Modeling Management Metadata 70

AWS Big Data

AUGUST 1, 2024

However, you might face significant challenges when planning for a large-scale data warehouse migration. This includes the ETL processes that capture source data, the functional refinement and creation of data products, the aggregation for business metrics, and the consumption from analytics, business intelligence (BI), and ML.

Data Warehouse 114

Data Warehouse KPI Optimization Cost-Benefit 114

CIO Business Intelligence

DECEMBER 6, 2023

However, this partnership model cannot keep pace with an always-changing technology landscape in which the skill gaps and lack of resources are increasing. The new models recognise this, drawing tech vendors to shift toward innovation-focused roles and become partners in the client’s success.

Digital Transformation 116

Digital Transformation Software Cost-Benefit Manufacturing 116

Cloudera

OCTOBER 8, 2024

This service supports a range of optimized AI models, enabling seamless and scalable AI inference. Enterprise developers began exploring proof of concepts (POCs) for generative AI applications, leveraging API services and open models such as Llama 2 and Mistral. By 2023, the focus shifted towards experimentation.

Optimization 75

Optimization Experimentation Metrics Enterprise 75

Cloudera

OCTOBER 13, 2020

Data Warehouse – in addition to a number of performance optimizations, DW has added a number of new features for better scalability, monitoring and reliability to enable self-service access with security and performance . Predict – Data Engineering (Apache Spark). New Services. Learn More, Keep in Touch.

Data Warehouse 97

Data Warehouse Machine Learning Visualization Data Lake 97

Ontotext

MARCH 27, 2024

For example, GPS, social media, cell phone handoffs are modeled as graphs while data catalogs, data lineage and MDM tools leverage knowledge graphs for linking metadata with semantics. Knowledge graphs model knowledge of a domain as a graph with a network of entities and relationships.

Modeling 53

Modeling Metadata Data Quality Enterprise 53

CIO Business Intelligence

FEBRUARY 16, 2023

“All they would have to do is just build their model and run with it,” he says. But to augment its various businesses with ML and AI, Iyengar’s team first had to break down data silos within the organization and transform the company’s data operations. For now, it operates under a centralized “hub and spokes” model.

Unstructured Data 105

Unstructured Data Data Lake Prescriptive Analytics Data Warehouse 105

AWS Big Data

NOVEMBER 16, 2023

As with all AWS services, Amazon Redshift is a customer-obsessed service that recognizes there isn’t a one-size-fits-all for customers when it comes to data models, which is why Amazon Redshift supports multiple data models such as Star Schemas, Snowflake Schemas and Data Vault. Data Vault 2.0

Enterprise 110

Enterprise Data Warehouse Data Lake Optimization 110

CIO Business Intelligence

JUNE 29, 2022

If you can’t make sense of your business data, you’re effectively flying blind. Insights hidden in your data are essential for optimizing business operations, finetuning your customer experience, and developing new products — or new lines of business, like predictive maintenance. Azure Data Factory.

Data Lake 116

Data Lake Analytics Data Warehouse Machine Learning 116

David Menninger's Analyst Perspectives

NOVEMBER 7, 2024

The difference is in using advanced modeling and data management to make faster scenario planning possible, driven by actionable key performance measures that enable faster, well-informed decision cycles. In tech speak, this means the semantic layer is optimized for the intended audience.

Forecasting 130

Forecasting Machine Learning Finance Predictive Analytics 130

AWS Big Data

SEPTEMBER 5, 2024

With auto-copy, automation enhances the COPY command by adding jobs for automatic ingestion of data. If storing operational data in a data warehouse is a requirement, synchronization of tables between operational data stores and Amazon Redshift tables is supported.

IoT 111

IoT Data Warehouse Cost-Benefit Reporting 111

Sisense

OCTOBER 15, 2020

Let’s look at a few ways that different industries take advantage of streaming data. How industries can benefit from streaming data. Automotive: Monitoring connected, autonomous cars in real time to optimize routes to avoid traffic and for diagnosis of mechanical issues. Optimizing object storage.

Dashboards 98

Dashboards IoT Optimization Internet of Things 98

Ontotext

DECEMBER 9, 2020

We all want to solve the interesting data challenges, build analytics, generate graph embeddings and train smart machine learning models over our knowledge graph data. They allow Ontotext to perform optimizations that are not easy/possible using an ORM embedded within a custom-built API.

Modeling 130

Modeling Management Optimization Machine Learning 130

Cloudera

JULY 21, 2022

Cloudera users can securely connect Rill to a source of event stream data, such as Cloudera DataFlow , model data into Rill’s cloud-based Druid service, and share live operational dashboards within minutes via Rill’s interactive metrics dashboard or any connected BI solution. Cloudera Data Warehouse). Apache Hive.

Metrics 87

Metrics Slice and Dice Data Warehouse Dashboards 87

AWS Big Data

AUGUST 19, 2024

In this post, we explore how AWS Glue can serve as the data integration service to bring the data from Snowflake for your data integration strategy, enabling you to harness the power of your data ecosystem and drive meaningful outcomes across various use cases. Store the extracted and transformed data in Amazon S3.

Analytics 119

Analytics Data-driven Data Integration Data Lake 119

Cloudera

DECEMBER 21, 2021

Since the release of Cloudera Data Engineering (CDE) more than a year ago , our number one goal was operationalizing Spark pipelines at scale with first class tooling designed to streamline automation and observability. This enabled new use-cases with customers that were using a mix of Spark and Hive to perform data transformations. .

Snapshot 118

Snapshot Data-driven Optimization Data Architecture 118

CIO Business Intelligence

JANUARY 24, 2024

At Vanguard, “data and analytics enable us to fulfill on our mission to provide investors with the best chance for investment success by enabling us to glean actionable insights to drive personalized client experiences, scale advice, optimize investment and business operations, and reduce risk,” Swann says.

Data Strategy 136

Data Strategy Strategy Unstructured Data Data Governance 136

AWS Big Data

JULY 20, 2023

This data is then used by various applications for streaming analytics, business intelligence, and reporting. Amazon SageMaker is used to build, train, and deploy a range of ML models. This ensures that the data is suitable for training purposes. Additionally, SageMaker training jobs are employed for training the models.

Data Lake 98

Data Lake Analytics Snapshot Data Quality 98

Cloudera

JUNE 24, 2024

The complexities of modern data workflows often translate into countless hours spent coding, debugging, and optimizing models. Recognizing this pain point, we set out to redefine the data science experience with AI-driven innovation.

Machine Learning 72

Machine Learning Data Science Data-driven Testing 72

Occam's Razor

OCTOBER 19, 2010

A huge vast majority of clicks coming from search engines continue to be organic clicks (which is why I love and adore search engine optimization). Google Website Optimizer. Here's a free guide – 26 pages – to use the website optimizer optimally: PDF Download: The Techie Guide to Google Website Optimizer.

Analytics 136

Analytics Testing Measurement Optimization 136

AWS Big Data

JANUARY 30, 2025

Pattern 1: Data transformation, load, and unload Several of our data pipelines included significant data transformation steps, which were primarily performed through SQL statements executed by Amazon Redshift. The following Diagram 2 shows this workflow.

Data Warehouse 53

Data Warehouse Data Architecture Machine Learning Data Transformation 53

IBM Big Data Hub

JULY 17, 2023

is our enterprise-ready next-generation studio for AI builders, bringing together traditional machine learning (ML) and new generative AI capabilities powered by foundation models. With watsonx.ai, businesses can effectively train, validate, tune and deploy AI models with confidence and at scale across their enterprise. IBM watsonx.ai

Machine Learning 62

Machine Learning Data Warehouse Modeling Cost-Benefit 62

Insight

APRIL 8, 2020

In some cases, they work to deploy data science models into production with an eye towards optimization, scalability and maintainability. Data architects and data modelers who specialize in areas such as schema design, identifying query access patterns and building and maintaining data warehouses.

Data Warehouse 96

Data Warehouse Cost-Benefit Software Optimization 96