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. If we talk about Big Data, data visualization is crucial to more successfully drive high-level decision making.

Visualization 145

Visualization Cost-Benefit Big Data Prescriptive Analytics 145

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 Data Analytics 130

AWS Big Data

JANUARY 6, 2025

With Amazon AppFlow, you can run data flows at nearly any scale and at the frequency you chooseon a schedule, in response to a business event, or on demand. You can configure data transformation capabilities such as filtering and validation to generate rich, ready-to-use data as part of the flow itself, without additional steps.

Analytics 94

Analytics Data Warehouse Big Data Metrics 94

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 Analytics Data Warehouse Data Processing 52

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 101

Metadata Data Lake Visualization Data Quality 101

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 110

Analytics Visualization Data Integration Cost-Benefit 110

AWS Big Data

AUGUST 19, 2024

As organizations increasingly rely on data stored across various platforms, such as Snowflake , Amazon Simple Storage Service (Amazon S3), and various software as a service (SaaS) applications, the challenge of bringing these disparate data sources together has never been more pressing.

Analytics 107

Analytics Data-driven Data Integration Data Lake 107

AWS Big Data

DECEMBER 21, 2023

Movement of data across data lakes, data warehouses, and purpose-built stores is achieved by extract, transform, and load (ETL) processes using data integration services such as AWS Glue. AWS Glue provides both visual and code-based interfaces to make data integration effortless.

Analytics 107

Analytics IT Data Lake Visualization 107

AWS Big Data

NOVEMBER 13, 2023

The downstream consumers consist of business intelligence (BI) tools, with multiple data science and data analytics teams having their own WLM queues with appropriate priority values. Consequently, there was a fivefold rise in data integrations and a fivefold increase in ad hoc queries submitted to the Redshift cluster.

Data Warehouse 104

Data Warehouse Analytics Data Lake Data Science 104

AWS Big Data

NOVEMBER 7, 2023

For these, AWS Glue provides fast, scalable data transformation. Third, AWS continues adding support for more data sources including connections to software as a service (SaaS) applications, on-premises applications, and other clouds so organizations can act on their data. Visit Data integration with AWS to learn more.

Dashboards 80

Dashboards Data-driven Data Integration Data Lake 80

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. This empowers data users to make decisions informed by data and in real-time with increased confidence.”

Data Strategy 136

Data Strategy Strategy Unstructured Data Data Governance 136

AWS Big Data

AUGUST 13, 2024

In today’s data-driven world, seamless integration and transformation of data across diverse sources into actionable insights is paramount. We will create a glue studio job, add events and venue data from the SFTP server, carry out data transformations and load transformed data to s3.

Data Processing 98

Data Processing Visualization Data Lake Data Processing 98

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 110

Visualization Dashboards Data-driven Gap analysis 110

Ontotext

MARCH 20, 2024

In today’s data-driven world, businesses are drowning in a sea of information. Traditional data integration methods struggle to bridge these gaps, hampered by high costs, data quality concerns, and inconsistencies. Unleashing the Power of Data Connections Zenia Graph isn’t just another data solution company.

Data-driven 52

Data-driven Strategy Sales Data Integration 52

AWS Big Data

SEPTEMBER 13, 2024

To share data to our internal consumers, we use AWS Lake Formation with LF-Tags to streamline the process of managing access rights across the organization. Data integration workflow A typical data integration process consists of ingestion, analysis, and production phases.

Interactive 86

Interactive Strategy Cost-Benefit Data Governance 86

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

FineReport

JUNE 7, 2024

FineReport : Enterprise-Level Reporting and Dashboard Software Try FineReport Now In 2024, FanRuan continues to push boundaries with groundbreaking advancements in AI-driven analytics and real-time data analytics processing. Elevate your data transformation journey with Dataiku’s comprehensive suite of solutions.

Visualization 52

Visualization Predictive Analytics Dashboards Predictive Modeling 52

AWS Big Data

JULY 20, 2023

Specifically, the system uses Amazon SageMaker Processing jobs to process the data stored in the data lake, employing the AWS SDK for Pandas (previously known as AWS Wrangler) for various data transformation operations, including cleaning, normalization, and feature engineering.

Data Lake 93

Data Lake Analytics Snapshot Data Quality 93

AWS Big Data

JULY 31, 2023

Customers often use many SQL scripts to select and transform the data in relational databases hosted either in an on-premises environment or on AWS and use custom workflows to manage their ETL. AWS Glue is a serverless data integration and ETL service with the ability to scale on demand.

Sales 52

Sales Data Warehouse Visualization Testing 52

Jet Global

MAY 9, 2024

A data pipeline is a series of processes that move raw data from one or more sources to one or more destinations, often transforming and processing the data along the way. 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

MAY 1, 2023

Third-party data might include industry benchmarks, data feeds (such as weather and social media), and/or anonymized customer data. Four Approaches to Data Analytics The world of data analytics is constantly and quickly changing. Data Transformation and Enrichment Data can be enriched for analysis.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52

Jet Global

JULY 16, 2024

Apache Iceberg is an open table format for huge analytic datasets designed to bring high-performance ACID (Atomicity, Consistency, Isolation, and Durability) transactions to big data. It provides a stable schema, supports complex data transformations, and ensures atomic operations. What is Apache Iceberg?

Dashboards 52

Dashboards Data-driven Reporting Business Intelligence 52

AWS Big Data

JANUARY 29, 2025

times more performant than Apache Spark 3.5.1), and ease of Amazon EMR with the control and proximity of your data center, empowering enterprises to meet stringent regulatory and operational requirements while unlocking new data processing possibilities. This method is ideal for recurring tasks or large-scale data transformations.

Big Data 68

Big Data Data Analytics Analytics Interactive 68

DataKitchen

JANUARY 23, 2023

Only then can you tell the true impact of a column name change on the data transformations, the models, and the visualization you give to your customers. We must do the same as data analytic teams. Data lineage does not directly improve data quality. Though valuable, Data Quality scores are largely static.

Testing 130

Testing Data Governance Data Quality Data-driven 130