FineReport

MARCH 31, 2024

In 2024, business intelligence (BI) software has undergone significant advancements, revolutionizing data management and decision-making processes. Throughout this article, we will delve into beginner-friendly options and unveil the top ten BI software solutions that streamline operations and provide a competitive edge.

Dashboards 52

Dashboards Visualization Data mining Data-driven 52

AWS Big Data

APRIL 26, 2023

The data enrichment starts with an Oracle Database (Software Parts) that contains part numbers that are related to software. Because semiconductors are the basis for running software, this database builds the foundation of our data processing. The following diagram illustrates the approach.

Forecasting 124

Forecasting Manufacturing Data Lake Big Data 124

AWS Big Data

MAY 9, 2023

For workloads such as data transforms, joins, and queries, you can use G.1X With exponentially growing data sources and data lakes, customers want to run more data integration workloads, including their most demanding transforms, aggregations, joins, and queries. 1X (1 DPU) and G.2X DPU-hour ($) G.2X

Data Lake 92

Data Lake Cost-Benefit Data Integration Data Transformation 92

datapine

MAY 2, 2023

Your Chance: Want to test a professional logistics analytics software? Use our 14-days free trial today & transform your supply chain! Your Chance: Want to test a professional logistics analytics software? Use our 14-days free trial today & transform your supply chain! Now’s the time to strike.

Big Data 275

Big Data Cost-Benefit Internet of Things Optimization 275

AWS Big Data

NOVEMBER 29, 2023

dbt is an open source, SQL-first templating engine that allows you to write repeatable and extensible data transforms in Python and SQL. dbt is predominantly used by data warehouses (such as Amazon Redshift ) customers who are looking to keep their data transform logic separate from storage and engine.

Data Lake 107

Data Lake Management Metrics Data Warehouse 107

AWS Big Data

SEPTEMBER 19, 2023

This is a guest post by Khandu Shinde, Staff Software Engineer and Edward Paget, Senior Software Engineering at Chime Financial. Edward Paget is a Software Engineer working on building Chime’s capabilities to mitigate risk to ensure our members’ financial peace of mind.

Analytics 82

Analytics Risk Big Data Machine Learning 82

CIO Business Intelligence

JANUARY 12, 2023

Each strategy will be different according to the unique needs of the university, but at a minimum it should include the following: Evaluation of current data estate to understand pinch points and siloes so these can start to be tackled. Comprehensive upskilling programme to overcome data skills gaps.

Data Strategy 80

Data Strategy Strategy IT Consulting 80

DataKitchen

DECEMBER 9, 2022

Both DevOps and DataOps are approaches to managing and optimizing the development and deployment of software and other applications, with a focus on collaboration, automation, and continuous improvement. Query> Is DataOps something that can be solved with software or is it more of a people process?

Machine Learning 130

Machine Learning Data-driven Optimization Modeling 130

AWS Big Data

AUGUST 1, 2023

In the world of software engineering and development, organizations use project management tools like Atlassian Jira Cloud. This post shows you how to use Amazon AppFlow and AWS Glue to create a fully automated data ingestion pipeline that will synchronize your Jira data into your data lake. Choose Update.

Data Lake 87

Data Lake Data Transformation Cost-Benefit Data-driven 87

IBM Big Data Hub

JULY 28, 2023

As an independent software vendor (ISV), we at Primeur embed the Open Liberty Java runtime in our flagship data integration platform, DATA ONE. Data Shaper , providing any-to-any data transformations. Data Watcher , for the integrated end-to-end monitoring of dataflows. Why invisibility?

Data Integration 58

Data Integration Optimization Software Insurance 58

CIO Business Intelligence

JULY 5, 2022

What is the difference between business analytics and data analytics? Business analytics is a subset of data analytics. Data analytics is used across disciplines to find trends and solve problems using data mining , data cleansing, data transformation, data modeling, and more.

Business Analytics 125

Business Analytics Prescriptive Analytics Data mining Diagnostic Analytics 125

DataKitchen

OCTOBER 5, 2021

The data organization wants to run the Value Pipeline as robustly as a six sigma factory, and it must be able to implement and deploy process improvements as rapidly as a Silicon Valley start-up. The data engineer builds data transformations. Their product is the data. Unlike software dev, data can’t be automated.

Testing 152

Testing Dashboards Measurement Experimentation 152

FineReport

APRIL 21, 2024

In today’s data-driven landscape, businesses are constantly seeking innovative solutions to harness the power of analytics effectively. Embedded BI tools have emerged as a transformative force, seamlessly integrating analytical capabilities directly into existing software applications.

Dashboards 52

Dashboards Visualization Interactive Business Intelligence 52

CIO Business Intelligence

JANUARY 24, 2024

Overlooking these data resources is a big mistake. The proper use of unstructured data will become of increasing importance to IT leaders,” says Kevin Miller, CTO of enterprise software developer IFS. “It This empowers data users to make decisions informed by data and in real-time with increased confidence.”

Data Strategy 134

Data Strategy Strategy Unstructured Data Data Governance 134

CIO Business Intelligence

JUNE 7, 2022

Data analytics draws from a range of disciplines — including computer programming, mathematics, and statistics — to perform analysis on data in an effort to describe, predict, and improve performance. What are the four types of data analytics?

Data Analytics 128

Data Analytics Diagnostic Analytics Management Analytics 128

AWS Big Data

NOVEMBER 7, 2023

Second, organizations still need transformations like cleansing, deduplication, and combining datasets for analysis and machine learning (ML). For these, AWS Glue provides fast, scalable data transformation.

Dashboards 75

Dashboards Data-driven Data Integration Data Lake 75

AWS Big Data

JULY 26, 2023

To tackle these asks, this post defines the development lifecycle for data integration and demonstrates how software engineers and data engineers can design an end-to-end development lifecycle using AWS Glue, including development, testing, and CI/CD, using a sample baseline template.

Data Integration 74

Data Integration Snapshot Testing Visualization 74

AWS Big Data

DECEMBER 21, 2023

The data products from the Business Vault and Data Mart stages are now available for consumers. smava decided to use Tableau for business intelligence, data visualization, and further analytics. The data transformations are managed with dbt to simplify the workflow governance and team collaboration.

Data Lake 93

Data Lake Data Warehouse Data-driven B2B 93

AWS Big Data

SEPTEMBER 6, 2023

Stored procedures are commonly used to encapsulate logic for data transformation, data validation, and business-specific logic. He has over 17 years of experience in building data assets and leading complex data platform programs for banking and insurance clients across the globe.

Data Warehouse 100

Data Warehouse Insurance Statistics Software 100

Insight

APRIL 8, 2020

Having run a data engineering program at Insight for several years, we’ve identified three broad categories of data engineers: Software engineers who focus on building data pipelines. In some cases, they work to deploy data science models into production with an eye towards optimization, scalability and maintainability.

Cost-Benefit 96

Cost-Benefit Software Data Warehouse Optimization 96

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. Neel Patel is a software engineer working within GlueML. Edward Cho is a Software Development Engineer at AWS Glue.

Data Quality 76

Data Quality Metrics Data-driven Visualization 76

Ontotext

FEBRUARY 12, 2024

For many organizations, a centralized data platform will fall short as it gives data teams much less autonomy over managing increasingly diverse and voluminous datasets. Centralized teams also adopted an auditing mechanism to verify data accuracy and adherence to SLAs and to ensure data quality. Intuit, a U.S.

Data-driven 59

Data-driven Data Lake Data Quality Business Objectives 59

AWS Big Data

APRIL 25, 2023

Implementing an effective data sharing strategy that satisfies compliance and regulatory requirements is complex. Customers often need to share data between disparate software as a service (SaaS) platforms within their organization or across organizations.

Sales 74

Sales Visualization Software Marketing 74

Sisense

MARCH 30, 2021

Advanced data transformation with Custom Code. With our latest release, you can leverage Python code from Jupyter Notebooks to connect to services such as Amazon SageMaker, Amazon Comprehend, and Amazon Translate to transform and augment data inside your ElastiCube models. If so, it’s your lucky day.

Dashboards 52

Dashboards Machine Learning Data Warehouse Marketing 52

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. In this post, we focus on data migration and ongoing transformation.

Data Warehouse 40

Data Warehouse Testing Strategy Data-driven 40

erwin

SEPTEMBER 17, 2020

Data automation reduces the loss of time in collecting, processing and storing large chunks of data because it replaces manual processes (and human errors) with intelligent processes, software and artificial intelligence (AI).

Cost-Benefit 143

Cost-Benefit Data Governance Metadata Reporting 143

Jen Stirrup

SEPTEMBER 30, 2021

AI vs ML vs Data Science vs Business Intelligence. Before we dive in, let’s define strands of AI, Machine Learning and Data Science: Business intelligence (BI) leverages software and services to transform data into actionable insights that inform an organization’s strategic and tactical business decisions.

Business Intelligence 135

Business Intelligence Data mining Machine Learning Testing 135

AWS Big Data

MARCH 13, 2024

You can also use the data transformation feature of Data Firehose to invoke a Lambda function to perform data transformation in batches. You can now explore extending this sample code with your own device tracking data and analytics requirements.

Analytics 99

Analytics IoT Metadata Internet of Things 99

AWS Big Data

OCTOBER 5, 2023

In today’s data-driven world, the ability to effortlessly move and analyze data across diverse platforms is essential. Amazon AppFlow , a fully managed data integration service, has been at the forefront of streamlining data transfer between AWS services, software as a service (SaaS) applications, and now Google BigQuery.

Data Warehouse 89

Data Warehouse Machine Learning Data Integration Data-driven 89

AWS Big Data

APRIL 12, 2023

She is an experienced analytics leader working with AWS customers to provide best practice guidance and technical advice in order to assist their success in data transformation. Her areas of interests are open-source frameworks and automation, data engineering and DataOps.

Testing 77

Testing Big Data Metadata Optimization 77

IBM Big Data Hub

OCTOBER 16, 2023

A data store lets a business connect existing data with new data and discover new insights with real-time analytics and business intelligence. It helps you streamline data engineering with reduced data pipelines, simplified data transformation and enriched data.

Risk 75

Risk Modeling Management Metadata 75

Cloudera

APRIL 12, 2021

Data access is enabled through the smart implementation of cloud, which in turn allows for faster and more informed decision-making. We had our cloud environment, enterprise services [and Software-as-a-Service] infrastructure all set up so we could get services out centrally…across the whole U.S.,”

Enterprise 52

Enterprise IT Digital Transformation Data Warehouse 52

AWS Big Data

JULY 25, 2023

As well as Talend Cloud for enterprise-level data transformation needs, you could also use Talend Stitch to handle data ingestion and data replication to Redshift Serverless. All configuration for ingestion or replicating data from your desired sources to Redshift Serverless is done in a single input screen.

Data Analytics 52

Data Analytics Data Warehouse Analytics Data Processing 52

Cloudera

FEBRUARY 8, 2021

This is purely an example of how to develop a solution using Cloudera’s software. . Main components used in this demo: Cloudera Operational Database (COD), as mentioned in my previous post, is a managed dbPaaS solution available as an experience in Cloudera Data Platform (CDP). b) Basic data transformation. and run it.

Machine Learning 72

Machine Learning Statistics Modeling Dashboards 72

O'Reilly on Data

JANUARY 17, 2023

What would you say is the job of a software developer? A layperson, an entry-level developer, or even someone who hires developers will tell you that job is to … well … write software. They’d say that the job involves writing some software, sure. But deep down it’s about the purpose of software. Pretty simple.

Machine Learning 325

Machine Learning Predictive Modeling Software Modeling 325

AWS Big Data

FEBRUARY 21, 2023

We use Apache Spark as our main data processing engine and have over 1,000 Spark applications running over massive amounts of data every day. These Spark applications implement our business logic ranging from data transformation, machine learning (ML) model inference, to operational tasks. Their costs were climbing.

Cost-Benefit 56

Cost-Benefit Informatics Optimization Management 56

AWS Big Data

APRIL 19, 2023

This approach creates a truly connected ecosystem with simplified access to delight your data consumers. The current solution is platform agnostic; however, in a future post we will show how to implement this using data.all (open-source software) and Amazon DataZone.

Technology 85

Technology Data-driven Machine Learning Sales 85