AWS Big Data

DECEMBER 21, 2023

smava believes in and takes advantage of data-driven decisions in order to become the market leader. The Data Platform team is responsible for supporting data-driven decisions at smava by providing data products across all departments and branches of the company.

Data Lake 115

Data Lake Data Warehouse Data-driven B2B 115

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

FEBRUARY 16, 2023

“Digitizing was our first stake at the table in our data journey,” he says. That step, primarily undertaken by developers and data architects, established data governance and data integration. For that, he relied on a defensive and offensive metaphor for his data strategy.

Unstructured Data 105

Unstructured Data Data Lake Prescriptive Analytics Data Warehouse 105

IBM Big Data Hub

JUNE 15, 2023

It is comprised of commodity cloud object storage, open data and open table formats, and high-performance open-source query engines. To help organizations scale AI workloads, we recently announced IBM watsonx.data , a data store built on an open data lakehouse architecture and part of the watsonx AI and data platform.

Data Warehouse 86

Data Warehouse Data Lake Optimization Data-driven 86

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. These upstream data sources constitute the data producer components.

Data Warehouse 111

Data Warehouse Analytics Data Lake Data Science 111

Cloudera

JULY 21, 2022

Co-author: Mike Godwin, Head of Marketing, Rill Data. Cloudera has partnered with Rill Data, an expert in metrics at any scale, as Cloudera’s preferred ISV partner to provide technical expertise and support services for Apache Druid customers. Cloudera Data Warehouse). Efficient batch data processing.

Metrics 87

Metrics Slice and Dice Data Warehouse Dashboards 87

AWS Big Data

DECEMBER 4, 2024

These nodes can implement analytical platforms like data lake houses, data warehouses, or data marts, all united by producing data products. Divisions decide how many domains to have within their node; some may have one, others many. Nodes and domains serve business needs and are not technology mandated.

Metadata 105

Metadata Data Governance Data Quality Data-driven 105

CIO Business Intelligence

JANUARY 9, 2023

To fuel self-service analytics and provide the real-time information customers and internal stakeholders need to meet customers’ shipping requirements, the Richmond, VA-based company, which operates a fleet of more than 8,500 tractors and 34,000 trailers, has embarked on a data transformation journey to improve data integration and data management.

Data Strategy 111

Data Strategy Strategy Data Governance Marketing 111

CIO Business Intelligence

AUGUST 3, 2023

When global technology company Lenovo started utilizing data analytics, they helped identify a new market niche for its gaming laptops, and powered remote diagnostics so their customers got the most from their servers and other devices. Each of the acquired companies had multiple data sets with different primary keys, says Hepworth. “We

Analytics 98

Analytics Data Lake Metadata Cost-Benefit 98

Octopai

NOVEMBER 13, 2022

The modern data stack is a data management system built out of cloud-based data systems. A given modern data stack will usually include components for data ingestion from your data sources, data transformation, data storage, data analysis and reporting.

Enterprise 97

Enterprise Data Warehouse Reporting Metadata 97

AWS Big Data

DECEMBER 21, 2023

As the volume and complexity of analytics workloads continue to grow, customers are looking for more efficient and cost-effective ways to ingest and analyse data. This enables organizations to streamline data integration and analytics with OpenSearch Service. Select the secret you created, and on the Actions menu, choose Delete.

Analytics 111

Analytics IT Data Lake Visualization 111

Alation

JANUARY 17, 2023

The modern data stack is a combination of various software tools used to collect, process, and store data on a well-integrated cloud-based data platform. It is known to have benefits in handling data due to its robustness, speed, and scalability. A typical modern data stack consists of the following: A data warehouse.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Science Data Transformation 52

AWS Big Data

SEPTEMBER 19, 2023

This creates a more competitive market with better, lower-cost options for everyday Americans who aren’t being served well by traditional banks. However, our legacy data warehouse-based solution was not equipped for this challenge. Chime partners with national banks to design member first financial products.

Analytics 109

Analytics Risk Big Data Machine Learning 109

Sisense

MARCH 30, 2021

As an analyst, developer, or even marketing or product leader, it’s more crucial now than ever to put personalized intelligence at the fingertips of the right stakeholders at the right place and time. Advanced data transformation with Custom Code. Parke Hunter is a Product Marketing Manager at Sisense.

Dashboards 52

Dashboards Machine Learning Data Warehouse Marketing 52

IBM Big Data Hub

JANUARY 18, 2023

This time, at least three different data platform solutions are emerging: Data Lakehouse, Data Fabric, and Data Mesh. While this is encouraging, it is also creating confusion in the market. Transformation must be performed continuously to keep the BLOB and data warehouse storage in sync, adding costs.

Data Lake 52

Data Lake Data Warehouse Data-driven Metadata 52

Alation

AUGUST 11, 2022

The data warehouse and analytical data stores moved to the cloud and disaggregated into the data mesh. Today, the brightest minds in our industry are targeting the massive proliferation of data volumes and the accompanying but hard-to-find value locked within all that data. Architectures became fabrics.

Metadata 52

Metadata Data Warehouse Data Quality Data Lake 52

IBM Big Data Hub

JULY 5, 2023

This was, without a question, a significant departure from traditional analytic environments, which often meant vendor-lock in and the inability to work with data at scale. Another unexpected challenge was the introduction of Spark as a processing framework for big data.

Data Lake 60

Data Lake Metadata Cost-Benefit Data Warehouse 60

Alation

OCTOBER 27, 2022

Few actors in the modern data stack have inspired the enthusiasm and fervent support as dbt. This data transformation tool enables data analysts and engineers to transform, test and document data in the cloud data warehouse. Bindu Chandramohan, Lead, Data Analytics, Alation : Thanks, Jason!

Metrics 52

Metrics Dashboards Sales Reporting 52

AWS Big Data

OCTOBER 18, 2023

Apache Hive is a distributed, fault-tolerant data warehouse system that enables analytics at a massive scale. Spark SQL is an Apache Spark module for structured data processing. Melody Yang is a Senior Big Data Solutions Architect for Amazon EMR at AWS.

Big Data 105

Big Data Data Processing Interactive Testing 105

IBM Big Data Hub

JULY 17, 2023

Capabilities within the Prompt Lab include: Summarize: Transform text with domain-specific content into personalized overviews and capture key points (e.g., It is supported by querying, governance, and open data formats to access and share data across the hybrid cloud.

Machine Learning 62

Machine Learning Data Warehouse Modeling Cost-Benefit 62

IBM Big Data Hub

MARCH 14, 2024

. With Db2 Warehouse’s fully managed cloud deployment on AWS, enjoy no overhead, indexing, or tuning and automated maintenance. Whether it’s for ad hoc analytics, data transformation, data sharing, data lake modernization or ML and gen AI, you have the flexibility to choose.

Cost-Benefit 75

Cost-Benefit Metadata Optimization Management 75

AWS Big Data

MARCH 3, 2023

The weeks that followed the lab included go-to-market activities with specific customers, documentation, hardening, security reviews, performance testing, data integrity testing, and automation activities. The Amazon S3 sink connector further streams data into Amazon S3 in real time by partitioning data into fixed-sized files.

Software 52

Software Data Lake Testing Cost-Benefit 52

Occam's Razor

OCTOBER 19, 2010

Disclosure:] I am the co-Founder of Market Motive Inc and the Analytics Evangelist for Google. None of these tools vendors have any relationship with Market Motive either. If after rigorous analysis you have determined that you have evolved to a stage that you need a data warehouse then you are out of luck with Yahoo!

Analytics 136

Analytics Testing Measurement Optimization 136

Jet Global

MAY 9, 2024

The key components of a data pipeline are typically: Data Sources : The origin of the data, such as a relational database , data warehouse, data lake , file, API, or other data store. 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

FEBRUARY 23, 2024

This field guide to data mapping will explore how data mapping connects volumes of data for enhanced decision-making. Why Data Mapping is Important Data mapping is a critical element of any data management initiative, such as data integration, data migration, data transformation, data warehousing, or automation.

Data Warehouse 52

Data Warehouse Reporting Data Transformation Visualization 52

Jet Global

MAY 1, 2023

Section 2: Embedded Analytics: No Longer a Want but a Need Section 3: How to be Successful with Embedded Analytics Section 4: Embedded Analytics: Build versus Buy Section 5: Evaluating an Embedded Analytics Solution Section 6: Go-to-Market Best Practices Section 7: The Future of Embedded Analytics Section 1: What are Embedded Analytics?

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52

Jet Global

AUGUST 9, 2023

Speed time to market with faster data migration, easier data transformation. Wands for SAP Wands for SAP empowers your finance team to leverage their existing Excel skills to streamline data entry to drive efficiencies in your month-end process. Time-to-value acceleration — Quick installation.

Finance 52

Finance Reporting Management Enterprise 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.

Dashboards 52

Dashboards Data Lake Reporting Cost-Benefit 52

Jet Global

OCTOBER 30, 2023

This shift toward these stand-alone business intelligence tools is motivated by a need for rapid, informed decision-making in the competitive business landscape, allowing organizations to adapt swiftly to market changes and optimize their processes for better outcomes. Transforming Financial Reporting with Dynamic Dashboards Download Now 1.

Dashboards 52

Dashboards Reporting Operational Reporting Software 52

Jet Global

MARCH 14, 2024

Microsoft Fabric offers a unified platform for data engineering, science, and analytics, integrating data from Power BI, Azure Synapse, and Azure Data Factory, and using open storage for accessibility and portability. It offers a transparent and accurate view of how data flows through the system, ensuring robust compliance.

Analytics 52

Analytics Management Reporting Data Quality 52

BI-Survey

MARCH 6, 2025

While efficiency is a priority, data quality and security remain non-negotiable. Developing and maintaining data transformation pipelines are among the first tasks to be targeted for automation. However, caution is advised since accuracy, timeliness, and other aspects of data quality depend on the quality of data pipelines.

Data Warehouse 52

Data Warehouse Metadata Unstructured Data Data-driven 52