DataKitchen

DECEMBER 20, 2020

Data-driven companies sense change through data analytics. Analytics tell the story of markets and customers. Analytics enable companies to understand their environment. Companies turn to their data organization to provide the analytics that stimulates creative problem-solving.

Data-driven 147

Data-driven Manufacturing Data Architecture Data Analytics 147

Sisense

FEBRUARY 26, 2020

We all know that data is becoming more and more essential for businesses, as the volume of data keeps growing. Dresner reported that nearly 97% of respondents in their Big Data Analytics Market Study consider Big Data to be either important or critical to their businesses.

Digital Transformation 90

Digital Transformation Analytics Cost-Benefit Data-driven 90

AWS Big Data

JUNE 29, 2023

Amazon Kinesis Data Analytics makes it easy to transform and analyze streaming data in real time. In this post, we discuss why AWS recommends moving from Kinesis Data Analytics for SQL Applications to Amazon Kinesis Data Analytics for Apache Flink to take advantage of Apache Flink’s advanced streaming capabilities.

Data Analytics 71

Data Analytics Analytics IoT Data Lake 71

CIO Business Intelligence

JANUARY 19, 2024

Whether you’re looking to earn a certification from an accredited university, gain experience as a new grad, hone vendor-specific skills, or demonstrate your knowledge of data analytics, the following certifications (presented in alphabetical order) will work for you. Not finding what you’re looking for?

Data Science 126

Data Science Machine Learning Predictive Modeling Experimentation 126

CIO Business Intelligence

MARCH 4, 2024

Stakeholders are currently waging an open debate across the industry of centralization versus federated data strategies. Proponents of centralization continue to assert its effectiveness in driving operational efficiencies, enhancing analytics effectiveness, and enabling governance crucial to data security, privacy, and regulatory compliance.

Insurance 90

Insurance Strategy Data Governance Data Integration 90

AWS Big Data

DECEMBER 13, 2023

In addition to using native managed AWS services that BMS didn’t need to worry about upgrading, BMS was looking to offer an ETL service to non-technical business users that could visually compose data transformation workflows and seamlessly run them on the AWS Glue Apache Spark-based serverless data integration engine.

Metadata 84

Metadata Data Lake Visualization Data Transformation 84

DataKitchen

DECEMBER 9, 2022

ChatGPT> DataOps, or data operations, is a set of practices and technologies that organizations use to improve the speed, quality, and reliability of their data analytics processes. Overall, DataOps is an essential component of modern data-driven organizations. Query> DataOps. Query> Write an essay on DataOps.

Machine Learning 130

Machine Learning Data-driven Optimization Modeling 130

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 Cost-Benefit Internet of Things Optimization 275

AWS Big Data

NOVEMBER 9, 2023

It does this by helping teams handle the T in ETL (extract, transform, and load) processes. It allows users to write data transformation code, run it, and test the output, all within the framework it provides. As part of their cloud modernization initiative, they sought to migrate and modernize their legacy data platform.

Data Warehouse 100

Data Warehouse Testing Data Quality Reporting 100

AWS Big Data

APRIL 2, 2024

You can use Amazon Data Firehose to aggregate and deliver log events from your applications and services captured in Amazon CloudWatch Logs to your Amazon Simple Storage Service (Amazon S3) bucket and Splunk destinations, for use cases such as data analytics, security analysis, application troubleshooting etc.

Metadata 81

Metadata Marketing Analytics Data Transformation 81

CIO Business Intelligence

JANUARY 24, 2024

Building a successful data strategy at scale goes beyond collecting and analyzing data,” says Ryan Swann, chief data analytics officer at financial services firm Vanguard. When different departments, business units, or groups keep data stored in systems not available to others, it diminishes the value of the data.

Data Strategy 136

Data Strategy Strategy Unstructured Data Data Governance 136

DataKitchen

OCTOBER 5, 2021

A DataOps Engineer owns the assembly line that’s used to build a data and analytic product. That’s the state of data analytics today. . Figure 2: Data operations can be conceptualized as a series of automated factory assembly lines. Where are the data engineers, scientists and analytics?

Testing 157

Testing Dashboards Measurement Experimentation 157

AWS Big Data

APRIL 26, 2023

For historic reasons, the required data for this aggregation step is siloed and represented differently in diverse systems. Because each source system and data type have its own schema and format, it’s particularly difficult to perform analytics based on this data.

Manufacturing 118

Manufacturing Forecasting Data Lake Big Data 118

Smart Data Collective

APRIL 29, 2020

The extraction of raw data, transforming to a suitable format for business needs, and loading into a data warehouse. Data transformation. This process helps to transform raw data into clean data that can be analysed and aggregated. Data analytics and visualisation.

Management 85

Management Data Warehouse Digital Transformation Dashboards 85

Sisense

MARCH 14, 2021

However, when investigating big data from the perspective of computer science research, we happily discover much clearer use of this cluster of confusing concepts. As we move from right to left in the diagram, from big data to BI, we notice that unstructured data transforms into structured data.

Big Data 52

Big Data IoT Data Warehouse Data-driven 52

AWS Big Data

APRIL 11, 2023

In this post, we discuss how to streamline inventory management forecasting systems with AWS managed analytics, AI/ML, and database services. Data transformation Data transformation is essential in inventory management and forecasting solutions for both data analysis around sales and inventory, as well as ML for forecasting.

Forecasting 72

Forecasting Management IoT Data-driven 72

Cloudera

JULY 21, 2022

As creators and experts in Apache Druid, Rill understands the data store’s importance as the engine for real-time, highly interactive analytics. Rill solves this with pipeline services and Rill Developer, a free SQL-based data modeler. Cloudera Data Warehouse). Large-scale high throughput analytics. Apache Hive.

Metrics 88

Metrics Slice and Dice Data Warehouse Dashboards 88

Ontotext

NOVEMBER 18, 2021

Picture this – you start with the perfect use case for your data analytics product. And all of them are asking hard questions: “Can you integrate my data, with my particular format?”, “How well can you scale?”, “How many visualizations do you offer?”. Nowadays, data analytics doesn’t exist on its own.

Visualization 98

Visualization Reporting Metadata Enterprise 98

AWS Big Data

JULY 25, 2023

Today, in order to accelerate and scale data analytics, companies are looking for an approach to minimize infrastructure management and predict computing needs for different types of workloads, including spikes and ad hoc analytics. Partner Solutions Architect in Data and Analytics at AWS.

Data Analytics 52

Data Analytics Data Warehouse Analytics Data Processing 52

Sisense

OCTOBER 15, 2020

We live in a world of data: There’s more of it than ever before, in a ceaselessly expanding array of forms and locations. Dealing with Data is your window into the ways data teams are tackling the challenges of this new world to help their companies and their customers thrive. billion market by 2025.

Dashboards 98

Dashboards IoT Optimization Internet of Things 98

AWS Big Data

AUGUST 9, 2023

The advent of rapid adoption of serverless data lake architectures—with ever-growing datasets that need to be ingested from a variety of sources, followed by complex data transformation and machine learning (ML) pipelines—can present a challenge. Besides work, he enjoys spending time with family, hiking & mountain biking.

Data Lake 83

Data Lake Metrics Testing Cost-Benefit 83

Ontotext

MARCH 20, 2024

Unleashing the Power of Data Connections Zenia Graph isn’t just another data solution company. We are pioneers in knowledge graphs – a revolutionary technology that goes beyond simple data analytics, aggregation, and reporting. Zenia Graph’s Salesforce Accelerator makes this a reality.

Data-driven 52

Data-driven Strategy Sales Data Integration 52

CIO Business Intelligence

JUNE 29, 2022

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. And as businesses contend with increasingly large amounts of data, the cloud is fast becoming the logical place where analytics work gets done.

Data Lake 114

Data Lake Analytics Data Warehouse Machine Learning 114

AWS Big Data

OCTOBER 27, 2023

Data integration is the foundation of robust data analytics. It encompasses the discovery, preparation, and composition of data from diverse sources. In the modern data landscape, accessing, integrating, and transforming data from diverse sources is a vital process for data-driven decision-making.

Analytics 92

Analytics Visualization Data Integration Cost-Benefit 92

AWS Big Data

OCTOBER 11, 2023

Organizations with legacy, on-premises, near-real-time analytics solutions typically rely on self-managed relational databases as their data store for analytics workloads. Near-real-time streaming analytics captures the value of operational data and metrics to provide new insights to create business opportunities.

Management 101

Management Metadata Analytics Dashboards 101

CDW Research Hub

OCTOBER 25, 2019

As we review data transformation and modernization strategies with our clients, we find many are investigating Snowflake as a data warehouse solution due to its ease of use, speed, and increased flexibility over a traditional data warehouse offering. Analytics and intelligence for business users and user adoption.

Data Warehouse 40

Data Warehouse Testing Strategy Data-driven 40

CIO Business Intelligence

DECEMBER 22, 2022

DataOps (data operations) is an agile, process-oriented methodology for developing and delivering analytics. It brings together DevOps teams with data engineers and data scientists to provide the tools, processes, and organizational structures to support the data-focused enterprise. What is DataOps?

Analytics 129

Analytics Machine Learning Software Data Quality 129

AWS Big Data

JUNE 6, 2023

Furthermore, it allows for necessary actions to be taken, such as rectifying errors in the data source, refining data transformation processes, and updating data quality rules. This proactive approach helps mitigate the risk of making decisions based on inaccurate information.

Data Quality 71

Data Quality Metrics Data-driven Visualization 71

AWS Big Data

JULY 31, 2023

This solution decouples the ETL and analytics workloads from our transactional data source Amazon Aurora, and uses Amazon Redshift as the data warehouse solution to build a data mart. This concludes creating data sources on the AWS Glue job canvas. Under Transforms , choose SQL Query.

Sales 52

Sales Data Warehouse Visualization Testing 52

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.

Data Warehouse 88

Data Warehouse Data Lake Analytics Data Science 88

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

Anmut

MARCH 24, 2022

We could give many answers, but they all centre on the same root cause: most data leaders focus on flashy technology and symptomatic fixes instead of approaching data transformation in a way that addresses the root causes of data problems and leads to tangible results and business success. It doesn’t have to be this way.

ROI 52

ROI Measurement Data-driven Data Transformation 52

AWS Big Data

FEBRUARY 6, 2023

Use case overview Migrating Hadoop workloads to Amazon EMR accelerates big data analytics modernization, increases productivity, and reduces operational cost. Refactoring coupled compute and storage to a decoupling architecture is a modern data solution. Jiseong Kim is a Senior Data Architect at AWS ProServe.

Cost-Benefit 52

Cost-Benefit Data Lake Dashboards Big Data 52

Smart Data Collective

JULY 25, 2019

Big Data is the Key to Hospital Management. Big data is changing the scope of hospital management. Healthcare providers are using machine learning, predictive analytics and other big data technologies to trim costs and improve the quality of care. However, all big data solutions are not created equally. Conclusion.

Big Data 96

Big Data Data Transformation Management Software 96

AWS Big Data

APRIL 30, 2024

Amazon Q Developer can now generate complex data integration jobs with multiple sources, destinations, and data transformations. Generated jobs can use a variety of data transformations, including filter, project, union, join, and custom user-supplied SQL. In his spare time, he enjoys cycling with his road bike.

Data Integration 98

Data Integration Data Lake Data Warehouse Software 98

AWS Big Data

JULY 20, 2023

One key component that plays a central role in modern data architectures is the data lake, which allows organizations to store and analyze large amounts of data in a cost-effective manner and run advanced analytics and machine learning (ML) at scale. To overcome these issues, Orca decided to build a data lake.

Data Lake 83

Data Lake Analytics Snapshot Optimization 83

AWS Big Data

OCTOBER 11, 2023

The data in the machine-readable files can provide valuable insights to understand the true cost of healthcare services and compare prices and quality across hospitals. The availability of machine-readable files opens up new possibilities for data analytics, allowing organizations to analyze large amounts of pricing data.

Visualization 92

Visualization Dashboards Data-driven Gap analysis 92