CIO Business Intelligence

AUGUST 3, 2023

But before consolidating the required data, Lenovo had to overcome concerns around sharing potentially sensitive information. Hoogar’s staff helped relieve such fears by educating employees that information included in the solution, such as notices of bug fixes or software updates, was already public.

Analytics 98

Analytics Data Lake Metadata Cost-Benefit 98

AWS Big Data

NOVEMBER 9, 2023

In this post, we delve into a case study for a retail use case, exploring how the Data Build Tool (dbt) was used effectively within an AWS environment to build a high-performing, efficient, and modern data platform. It does this by helping teams handle the T in ETL (extract, transform, and load) processes.

Data Warehouse 126

Data Warehouse Testing Data Quality Reporting 126

CIO Business Intelligence

NOVEMBER 7, 2023

For years, IT and business leaders have been talking about breaking down the data silos that exist within their organizations. Given the importance of sharing information among diverse disciplines in the era of digital transformation, this concept is arguably as important as ever. There’s also the issue of bias.

Data Warehouse 142

Data Warehouse Digital Transformation Data-driven Reporting 142

erwin

SEPTEMBER 17, 2020

Replace manual and recurring tasks for fast, reliable data lineage and overall data governance. It’s paramount that organizations understand the benefits of automating end-to-end data lineage. Critically, it makes it easier to get a clear view of how information is created and flows into, across and outside an enterprise.

Cost-Benefit 143

Cost-Benefit Data Governance Metadata Reporting 143

AWS Big Data

AUGUST 1, 2024

However, you might face significant challenges when planning for a large-scale data warehouse migration. The following diagram illustrates a scalable migration pattern for extract, transform, and load (ETL) scenario. The success criteria are the key performance indicators (KPIs) for each component of the data workflow.

Data Warehouse 115

Data Warehouse KPI Optimization Cost-Benefit 115

Sisense

AUGUST 28, 2020

Keeping data quality high ensures that the insights your end-users pull are aligned with reality and can help them (and the company at large) make smarter, d ata-driven decisions , as well as pipe quality information to customer-facing apps. . Process-driven data integrity: Getting data generation right.

Data Integration 101

Data Integration Testing Data Quality Data-driven 101

AWS Big Data

APRIL 19, 2023

Independent data products often only have value if you can connect them, join them, and correlate them to create a higher order data product that creates additional insights. A modern data architecture is critical in order to become a data-driven organization. Example use case Let’s walk through a concrete example.

Technology 105

Technology Data-driven Machine Learning Sales 105

AWS Big Data

SEPTEMBER 5, 2024

If storing operational data in a data warehouse is a requirement, synchronization of tables between operational data stores and Amazon Redshift tables is supported. In scenarios where data transformation is required, you can use Redshift stored procedures to modify data in Redshift tables.

IoT 111

IoT Data Warehouse Cost-Benefit Reporting 111

AWS Big Data

FEBRUARY 6, 2023

Then it retrieves the job history information (YARN logs from application managers) by calling the YARN ResourceManager application API. For more information on how to use the YARN log organizer, refer to the yarn-log-organizer GitHub repo. This information helps you understand who submits an application to a queue.

Dashboards 98

Dashboards Optimization Data Lake Cost-Benefit 98

AWS Big Data

NOVEMBER 15, 2023

For more information on this foundation, refer to A Detailed Overview of the Cost Intelligence Dashboard. The difference lies in when and where data transformation takes place. In ETL, data is transformed before it’s loaded into the data warehouse.

Analytics 111

Analytics Dashboards Metadata Data Warehouse 111

Cloudera

NOVEMBER 29, 2021

Data transforms businesses. That’s where the data lifecycle comes into play. Managing data and its flow, from the edge to the cloud, is one of the most important tasks in the process of gaining data intelligence. . The company needed a modern data architecture to manage the growing traffic effectively. .

Data Lake 77

Data Lake Data Warehouse Data Architecture Reporting 77

AWS Big Data

DECEMBER 21, 2023

Overview of solution As a data-driven company, smava relies on the AWS Cloud to power their analytics use cases. smava ingests data from various external and internal data sources into a landing stage on the data lake based on Amazon Simple Storage Service (Amazon S3).

Data Lake 115

Data Lake Data Warehouse Data-driven B2B 115

AWS Big Data

JULY 20, 2023

With data becoming the driving force behind many industries today, having a modern data architecture is pivotal for organizations to be successful. This ensures that the data is suitable for training purposes. table$manifests" Information about the data files: SELECT file_path, file_size_in_bytes FROM "db"."table$files"

Data Lake 98

Data Lake Analytics Snapshot Data Quality 98

AWS Big Data

NOVEMBER 13, 2023

The upstream data pipeline is a robust system that integrates various data sources, including Amazon Kinesis and Amazon Managed Streaming for Apache Kafka (Amazon MSK) for handling clickstream events, Amazon Relational Database Service (Amazon RDS) for delta transactions, and Amazon DynamoDB for delta game-related information.

Data Warehouse 111

Data Warehouse Analytics Data Lake Data Science 111

Peter James Thomas

MARCH 9, 2020

Obviously things improve as you climb up the “stairs” Of course organisations may be at a more advanced stage with respect to Data Controls than they are with Analytics. Equally one division or geographic territory might be at a different level with its Information than another.

Measurement 67

Measurement Data Strategy Strategy Modeling 67

Peter James Thomas

OCTOBER 30, 2018

Where they have, I have normally found the people holding these roles to be better informed about data matters than their peers. The closing sentence of the article is probably its most revealing and informative: […] marketers must make sure they are leading [the data] agenda, or someone else will do it for them.

Marketing 51

Marketing Strategy Data Architecture Data Strategy 51

Ontotext

FEBRUARY 12, 2024

Organizational culture is a key factor in determining the viability and success of a data mesh initiative. Empowering individual domains and integrating them as a cohesive whole requires a reevaluation of various aspects of the business, including how data and information are managed and shared.

Data-driven 59

Data-driven Data Lake Data Quality Business Objectives 59

FineReport

MARCH 31, 2024

Furthermore, these tools boast customization options, allowing users to tailor data sources to address areas critical to their business success, thereby generating actionable insights and customizable reports. Best BI Tools for Data Analysts 3.1 Key Features: Extensive library of pre-built connectors for diverse data sources.

Dashboards 52

Dashboards Visualization Data mining Data-driven 52

IBM Big Data Hub

FEBRUARY 9, 2023

In our last blog , we delved into the seven most prevalent data challenges that can be addressed with effective data governance. Today we will share our approach to developing a data governance program to drive data transformation and fuel a data-driven culture. Don’t try to do everything at once!

Data Governance 76

Data Governance Business Objectives Data Quality Measurement 76

AWS Big Data

FEBRUARY 6, 2023

Finally, we show you the technical information to use the tool. Use case overview Migrating Hadoop workloads to Amazon EMR accelerates big data analytics modernization, increases productivity, and reduces operational cost. The following diagram illustrates this architecture. For more information, see the GitHub repo.

Cost-Benefit 52

Cost-Benefit Data Lake Dashboards Big Data 52

erwin

APRIL 16, 2024

The data mesh framework In the dynamic landscape of data management, the search for agility, scalability, and efficiency has led organizations to explore new, innovative approaches. One such innovation gaining traction is the data mesh framework. This empowers individual teams to own and manage their data.

Metadata 52

Metadata Data Quality Data Governance Modeling 52

AWS Big Data

MARCH 3, 2023

Data ingestion – Steps 1 and 2 use AWS DMS, which connects to the source database and moves full and incremental data (CDC) to Amazon S3 in Parquet format. Data transformation – Steps 3 and 4 represent an EMR Serverless Spark application (Amazon EMR 6.9 Monjumi Sarma is a Data Lab Solutions Architect at AWS.

Data Lake 98

Data Lake Dashboards Metrics Metadata 98

IBM Big Data Hub

JANUARY 18, 2023

This adds an additional ETL step, making the data even more stale. Data lakehouse was created to solve these problems. The data warehouse storage layer is removed from lakehouse architectures. Instead, continuous data transformation is performed within the BLOB storage. Data mesh: A mostly new culture.

Data Lake 52

Data Lake Data Warehouse Data-driven Metadata 52

AWS Big Data

APRIL 5, 2023

The platform also provides analytics and insights to support successful information sharing and fuel continuous improvement. In 2021, Showpad decided to take the next step in its data evolution and set forth the vision to power innovation, product decisions, and customer engagement using data-driven insights.

Dashboards 52

Dashboards Reporting Cost-Benefit Visualization 52

CIO Business Intelligence

AUGUST 7, 2024

It’s not just returning a list of webpages, but it’s [giving users] richer content, and the content that’s produced through the generative AI search results allows [users] to go to parts of the web property that is the genesis of that information so they can dig deeper if they want,” says Michael A.

IT 119

IT Insurance Cost-Benefit Testing 119

Jet Global

MAY 1, 2023

Aggregated views of information may come from a department, function, or entire organization. These systems are designed for people whose primary job is data analysis. The data may come from multiple systems or aggregated views, but the output is a centralized overview of information. Who Uses Embedded Analytics?

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52

Jet Global

OCTOBER 1, 2024

Trino allows users to run ad hoc queries across massive datasets, making real-time decision-making a reality without needing extensive data transformations. This is particularly valuable for teams that require instant answers from their data. Data Lake Analytics: Trino doesn’t just stop at databases. Privacy Policy.

Dashboards 52

Dashboards Data Lake Reporting Cost-Benefit 52

AWS Big Data

DECEMBER 2, 2024

AWS Glue establishes a secure connection to HubSpot using OAuth for authorization and TLS for data encryption in transit. AWS Glue also supports the ability to apply complex data transformations, enabling efficient data integration and preparation to meet your needs. For Data sources , search for and select HubSpot.

Data Lake 105

Data Lake Testing Data Integration Metadata 105

AWS Big Data

MAY 12, 2025

Organizations worldwide aim to harness the power of data to drive smarter, more informed decision-making by embedding data at the core of their processes. Using data-driven insights enables you to respond more effectively to unexpected challenges, foster innovation, and deliver enhanced experiences to your customers.

Metrics 80

Metrics Cost-Benefit Metadata Data Lake 80

AWS Big Data

APRIL 28, 2025

However, migrating an existing data lake to a new table format such as Apache Iceberg can bring significant technical and organizational challenges Natural Intelligence (NI) is a world leader in multi-category marketplaces. com and BestMoney.com , help millions of people worldwide to make informed decisions every day.

Data Lake 68

Data Lake Metadata Cost-Benefit Snapshot 68

DataKitchen

JANUARY 23, 2023

Additionally, data lineage may not capture the impact of data errors on downstream systems or processes. For example, if an error in the data causes a downstream system to fail, data lineage may not capture this information. They are performed on the data during production runtime when it is actively processed.

Testing 130

Testing Data Governance Data Quality Data-driven 130

AWS Big Data

NOVEMBER 14, 2024

We use the built-in features of Data Firehose, including AWS Lambda for necessary data transformation and Amazon Simple Notification Service (Amazon SNS) for near real-time alerts. For more information, refer to Amazon Kinesis Data Firehose now supports zero buffering. Munim Abbasi is currently a Sr.

Data Lake 105

Data Lake Metadata Testing Data-driven 105