CIO Business Intelligence

JANUARY 20, 2023

Improved employee satisfaction: Providing business users access to data without having to contact analysts or IT can reduce friction, increase productivity, and facilitate faster results. BI aims to deliver straightforward snapshots of the current state of affairs to business managers.

Business Intelligence 144

Business Intelligence Dashboards Data mining OLAP 144

AWS Big Data

MARCH 2, 2023

Whenever there is an update to the Iceberg table, a new snapshot of the table is created, and the metadata pointer points to the current table metadata file. At the top of the hierarchy is the metadata file, which stores information about the table’s schema, partition information, and snapshots. all_reviews ): data and metadata.

Data Lake 128

Data Lake Data Processing Metadata Snapshot 128

AWS Big Data

DECEMBER 13, 2023

A CDC-based approach captures the data changes and makes them available in data warehouses for further analytics in real-time. usually a data warehouse) needs to reflect those changes in near real-time. This post showcases how to use streaming ingestion to bring data to Amazon Redshift.

Data Warehouse 111

Data Warehouse Snapshot Data Processing Internet of Things 111

CIO Business Intelligence

MAY 16, 2022

The advent of distributed workforces, smart devices, and internet-of-things (IoT) applications is creating a deluge of data generated and consumed outside of traditional centralized data warehouses. How edge refines data strategy. From there, other best practices emerge: Heighten the focus on security and governance.

IoT 98

IoT Internet of Things Data Warehouse Machine Learning 98

Cloudera

OCTOBER 11, 2022

Al needs machine learning (ML), ML needs data science. Data science needs analytics. And they all need lots of data. The takeaway – businesses need control over all their data in order to achieve AI at scale and digital business transformation. Doing data at scale requires a data platform. .

Data Science 94

Data Science Snapshot Data Warehouse Metadata 94

AWS Big Data

OCTOBER 18, 2023

Amazon Redshift is a fast, fully managed, petabyte-scale data warehouse that provides the flexibility to use provisioned or serverless compute for your analytical workloads. Modern analytics is much wider than SQL-based data warehousing. Fault tolerance is built in. Any hardware failures are automatically replaced.

Analytics 107

Analytics Data Warehouse Dashboards Testing 107

AWS Big Data

JUNE 28, 2023

There are two broad approaches to analyzing operational data for these use cases: Analyze the data in-place in the operational database (e.g. With Aurora zero-ETL integration with Amazon Redshift, the integration replicates data from the source database into the target data warehouse.

Data Warehouse 96

Data Warehouse Analytics Metrics Dashboards 96

AWS Big Data

AUGUST 1, 2024

Large-scale data warehouse migration to the cloud is a complex and challenging endeavor that many organizations undertake to modernize their data infrastructure, enhance data management capabilities, and unlock new business opportunities. This makes sure the new data platform can meet current and future business goals.

Data Warehouse 100

Data Warehouse KPI Optimization Cost-Benefit 100

Cloudera

AUGUST 21, 2024

This year, we’re excited to share that Cloudera’s Open Data Lakehouse 7.1.9 release was named a finalist under the category of Business Intelligence and Data Analytics. The root of the problem comes down to trusted data. Open Data Lakehouse also offers expanded support for Python 3.10 and RHEL 9.1,

Snapshot 66

Snapshot Unstructured Data Data Architecture Data Warehouse 66

AWS Big Data

JANUARY 8, 2024

This is the first post to a blog series that offers common architectural patterns in building real-time data streaming infrastructures using Kinesis Data Streams for a wide range of use cases. In this post, we will review the common architectural patterns of two use cases: Time Series Data Analysis and Event Driven Microservices.

Analytics 124

Analytics IoT Data-driven Snapshot 124

AWS Big Data

MAY 30, 2023

resource(“dynamodb”) table = dynamodb.Table(dydb_lookup_table) response = table.scan() items = response[“Items”] jsondata = sc.parallelize(items) lookupDf = glueContext.read.json(jsondata) return lookupDf # Load the Amazon Kinesis data stream from Amazon Glue Data Catalog. def readDynamoDb(): dynamodb = boto3.resource(“dynamodb”)

Data Lake 88

Data Lake Data Analytics Analytics Data Processing 88

AWS Big Data

JUNE 9, 2023

A modern data architecture enables companies to ingest virtually any type of data through automated pipelines into a data lake, which provides highly durable and cost-effective object storage at petabyte or exabyte scale. Clustering data for better data colocation using z-ordering.

Data Lake 125

Data Lake Metadata Statistics Optimization 125

AWS Big Data

OCTOBER 20, 2023

You can have multiple internal applications such as databases, data warehouses, or other systems where DNS names are not publicly resolvable. You can now use MSK Connect to privately connect with databases, data warehouses, and other resources in your VPC to comply with your security needs.

Data Processing 101

Data Processing Snapshot Data Warehouse Management 101

AWS Big Data

JANUARY 24, 2023

Data migration must be performed separately using methods such as S3 replication , S3 sync, aws-s3-copy-sync-using-batch or S3 Batch replication. This utility has two modes for replicating Lake Formation and Data Catalog metadata: on-demand and real-time. Nivas Shankar is a Principal Product Manager for AWS Lake Formation.

Data Architecture 73

Data Architecture Metadata Data Lake Snapshot 73

IBM Big Data Hub

SEPTEMBER 25, 2023

Presto was able to achieve this level of scalability by completely separating analytical compute from data storage. Presto is an open source distributed SQL query engine for data analytics and the data lakehouse, designed for running interactive analytic queries against datasets of all sizes, from gigabytes to petabytes.

OLAP 86

OLAP Data Lake Data-driven Online Analytical Processing 86

AWS Big Data

FEBRUARY 9, 2023

To achieve this, they combine their CRM data with a wealth of information already available in their data warehouse, enterprise systems, or other software as a service (SaaS) applications. One widely used approach is getting the CRM data into your data warehouse and keeping it up to date through frequent data synchronization.

Data Warehouse 87

Data Warehouse Data-driven Snapshot Testing 87

AWS Big Data

MARCH 25, 2024

Furthermore, data events are filtered, enriched, and transformed to a consumable format using a stream processor. The result is made available to the application by querying the latest snapshot. This allows the model to adapt to the latest changes in price and availability. versions).

Data Lake 105

Data Lake Unstructured Data Management Snapshot 105

Cloudera

NOVEMBER 15, 2024

However, there is a fundamental challenge standing in the way of being successful: data. By breaking down data silos and integrating log data from multiple sources, Cloudera empowers defenders with the real-time analytics to respond to threats swiftly.

Analytics 59

Analytics Metadata Snapshot Data-driven 59

AWS Big Data

MARCH 28, 2023

In a data warehouse, a dimension is a structure that categorizes facts and measures in order to enable users to answer business questions. This post is designed to be implemented for a real customer use case, where you get full snapshot data on a daily basis.

Data Lake 81

Data Lake Testing Snapshot Big Data 81

AWS Big Data

MARCH 3, 2023

Any time new test cases or test results are created or modified, events trigger such that processing is immediate and new snapshot files are available via an API or data is pulled at the refresh frequency of the reporting or business intelligence (BI) tool. Ricardo Serafim is a Senior AWS Data Lab Solutions Architect.

Software 52

Software Data Lake Testing Cost-Benefit 52

AWS Big Data

MARCH 3, 2023

You can then apply transformations and store data in Delta format for managing inserts, updates, and deletes. Amazon EMR Serverless is a serverless option in Amazon EMR that makes it easy for data analysts and engineers to run open-source big data analytics frameworks without configuring, managing, and scaling clusters or servers.

Data Lake 91

Data Lake Dashboards Metrics Metadata 91

AWS Big Data

NOVEMBER 1, 2023

Amazon Redshift is a fully managed, petabyte scale cloud data warehouse that enables you to analyze large datasets using standard SQL. Data warehouse workloads are increasingly being used with mission-critical analytics applications that require the highest levels of resilience and availability.

Data Warehouse 103

Data Warehouse Snapshot Testing Management 103

Corinium

APRIL 25, 2019

Ahead of the Chief Data Analytics Officers & Influencers, Insurance event we caught up with Dominic Sartorio, Senior Vice President for Products & Development, Protegrity to discuss how the industry is evolving. It definitely depends on the type of data, no one method is always better than the other.

Insurance 150

Insurance Risk IoT Data-driven 150

AWS Big Data

AUGUST 16, 2023

Time travel Time travel queries in Athena query Amazon S3 for historical data from a consistent snapshot as of a specified date and time. Version travel queries in Athena query Amazon S3 for historical data as of a specified snapshot ID. Karthikeyan Ramachandran is a Data Architect with AWS Professional Services.

Data Lake 79

Data Lake Metadata Testing Snapshot 79

Jet Global

NOVEMBER 14, 2022

That might be a sales performance dashboard for your Chief Revenue Officer, a snapshot of “days sales outstanding” (DSO) for the A/R collections team, or an item sales trend analysis for product management. With the CXO Data Warehouse Adapter, you can access ERP data, planning and budgeting numbers, or external information.

Reporting 52

Reporting Sales Dashboards Metrics 52

Jet Global

MAY 25, 2022

Every time you do an export from your ERP system, you’re taking a snapshot of the data that only reflects a single moment in time. A static (therefore outdated) view of the business : Another major problem with manual processes is that they don’t reflect what’s happening in the business in real time.

Reporting 52

Reporting Finance Software Snapshot 52

Jet Global

MAY 24, 2022

All of that in-between work–the export, the consolidation, and the cleanup–means that analysts are stuck using a snapshot of the data. Perhaps just as importantly, they lead to a time delay between the moment something happens in the business and the time it shows up on a report. Manual Processes Are Prone to Errors.

Finance 52

Finance Reporting Sales Software 52

Jet Global

MAY 4, 2022

There is yet another problem with manual processes: the resulting reports only reflect a snapshot in time. As soon as you export data from your ERP software or other business systems, it’s obsolete.

Reporting 52

Reporting Finance Software Consulting 52

Jet Global

MAY 2, 2022

The source data in this scenario represents a snapshot of the information in your ERP system. Researching that question requires substantial additional effort if your organization uses manual planning and budgeting processes. It’s not updated when someone records new transactions, and you can’t drill down to the details.

Sales 52

Sales Finance Reporting Software 52

Jet Global

NOVEMBER 3, 2022

Microsoft Excel offers flexibility, but it’s missing so many of the elements required to assemble data quickly and easily for powerful (and accurate) financial narratives. The reports created within static spreadsheets are based on a snapshot of reality, taken the moment the data was exported from ERP.

Finance 52

Finance Reporting Sales Dashboards 52

Jet Global

OCTOBER 27, 2022

And that is only a snapshot of the benefits your finance users will enjoy with Angles for Deltek. Angles has been effective to providing us real-time financial and operational data that otherwise we would have to manually parse together. Tools to configure custom views for the remaining 20% of your team’s operational reporting needs.

Operational Reporting 52

Operational Reporting Reporting Finance Dashboards 52

Cloudera

OCTOBER 10, 2024

The open data lakehouse is quickly becoming the standard architecture for unified multifunction analytics on large volumes of data. It combines the flexibility and scalability of data lake storage with the data analytics, data governance, and data management functionality of the data warehouse.

Optimization 84

Optimization Snapshot Data Lake Cost-Benefit 84

CIO Business Intelligence

NOVEMBER 25, 2024

“The data migration requires a lot of functional involvement and validation — working around month-end and fiscal year-end processes have been a challenge when the functional teams are also working to fill open roles on their teams,” Neumeier says. She realized HGA needed a data strategy, a data warehouse, and a data analytics leader.

Digital Transformation 131

Digital Transformation Data Warehouse Data Governance Enterprise 131

Cloudera

NOVEMBER 15, 2024

However, there is a fundamental challenge standing in the way of being successful: data. By breaking down data silos and integrating log data from multiple sources, Cloudera empowers defenders with the real-time analytics to respond to threats swiftly.

Analytics 84

Analytics Metadata Snapshot Data-driven 84

Cloudera

DECEMBER 3, 2024

Time Travel: Reproduce a query as of a given time or snapshot ID, which can be used for historical audits, validating ML models, and rollback of erroneous operations, as examples. Amazon Athena is a serverless, interactive analytics service that provides a simplified and flexible way to analyze petabytes of data where it lives.

Metadata 84

Metadata Data Warehouse ROI Snapshot 84