O'Reilly on Data

FEBRUARY 4, 2019

In a recent survey , we explored how companies were adjusting to the growing importance of machine learning and analytics, while also preparing for the explosion in the number of data sources. Data Platforms. Data Integration and Data Pipelines. Data preparation, data governance, and data lineage.

Machine Learning 277

Machine Learning Enterprise IoT Big Data 277

CIO Business Intelligence

MARCH 18, 2024

But when it comes to getting the most value out of hybrid cloud, one of the most crucial capabilities required is data replication and synchronization—what enables businesses to efficiently capture data changes and unify various data stores while ensuring low latency, high availability, and data integrity.

Cost-Benefit 85

Cost-Benefit Data Lake Machine Learning Data Integration 85

FineReport

JUNE 11, 2021

As companies striving to embrace digital transformation and become data-driven, business intelligence and analytics skills and experience are essential to building a data-savvy team. However, if someone puts you on the spot, can you clearly tell the difference between business intelligence and analytics? Definition.

Business Intelligence 52

Business Intelligence Analytics Dashboards Statistics 52

CIO Business Intelligence

OCTOBER 26, 2023

Business intelligence (BI) analysts transform data into insights that drive business value. This is done by mining complex data using BI software and tools , comparing data to competitors and industry trends, and creating visualizations that communicate findings to others in the organization.

Business Intelligence 126

Business Intelligence Data-driven Statistics Data Warehouse 126

CIO Business Intelligence

SEPTEMBER 2, 2022

The US financial services industry has fully embraced a move to the cloud, driving a demand for tech skills such as AWS and automation, as well as Python for data analytics, Java for developing consumer-facing apps, and SQL for database work. Software engineer. Full-stack software engineer. Back-end software engineer.

Finance 98

Finance IT Software Reporting 98

CIO Business Intelligence

AUGUST 31, 2022

The US financial services industry has fully embraced a move to the cloud, driving a demand for tech skills such as AWS and automation, as well as Python for data analytics, Java for developing consumer-facing apps, and SQL for database work. Software engineer. Full-stack software engineer. Back-end software engineer.

Finance 98

Finance IT Software Reporting 98

IBM Big Data Hub

SEPTEMBER 6, 2023

To ensure these scenarios remain actionable, they should be updated regularly based on the latest data and insights. Embracing technology The use of advanced solutions, ranging from AI-powered forecasting software to data analytics platforms, can make budgeting faster and smarter.

Forecasting 89

Forecasting Marketing Risk Sales 89

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. Overlooking these data resources is a big mistake. What’s the point of investing time and money on a strategy that lacks focus?

Data Strategy 134

Data Strategy Strategy Unstructured Data Data Governance 134

Jet Global

OCTOBER 28, 2021

Deal accelerates insightsoftware’s enterprise position in operational reporting by adding market-leading data analytics and integration products including SAP and Oracle ERP reporting solutions. The company’s data integration and connectivity solutions help customers better manage distributed data sources across the enterprise.

Operational Reporting 83

Operational Reporting Finance Data-driven Reporting 83

Cloudera

FEBRUARY 11, 2019

The January 2019 “Magic Quadrant for Data Management Solutions for Analytics” provides valuable insights into the status, direction, and players in the DMSA market. This applies to native CSP product offerings as well as point solutions from independent software vendors.”.

Management 42

Management Metadata Analytics Machine Learning 42

CIO Business Intelligence

MARCH 24, 2023

Your data governance program needs to continually break down new siloes. For more on these difficulties and others, see “ 7 data governance mistakes to avoid.” The tool that suits your enterprise will depend on your needs, data volume, and budget.

Data Governance 142

Data Governance Management Metadata Data Quality 142

Smart Data Collective

APRIL 20, 2020

According to a new study called Global Big Data Analytics in the Energy Sector Market, provides a comprehensive look at the industry. The value of data has become a primary focus for companies seeking an easy way to compromise. Effects of Analytics. Data can be used to change our world as well as the way we live and work.

Forecasting 96

Forecasting Uncertainty Big Data Marketing 96

AWS Big Data

MARCH 27, 2024

Achieving this will also improve general public health through better and more timely interventions, identify health risks through predictive analytics, and accelerate the research and development process. This will be your online transaction processing (OLTP) data store for transactional data.

Data Analytics 90

Data Analytics Analytics Data Warehouse Data Lake 90

AWS Big Data

AUGUST 15, 2023

As customers accelerate their migrations to the cloud and transform their businesses, some find themselves in situations where they have to manage data analytics in a multi-cloud environment, such as acquiring a company that runs on a different cloud provider. We use Athena to run queries on data stored on Google Cloud Storage.

Recreation/Entertainment 85

Recreation/Entertainment Unstructured Data Business Intelligence Data-driven 85

Ontotext

JANUARY 26, 2023

Secondly, by providing additional technical means to automate and facilitate seamless and smooth cooperation of heterogeneous and fragmented transportation actors and to enable them to operate on the web of transportation data.” As a result of these data quality issues, the need for integrity checks arises.

Interactive 52

Interactive Metadata Data Integration Data-driven 52

Jedox

FEBRUARY 13, 2020

The power of artificial intelligence (AI) lies within its ability to make sense of large amounts of data. For the increasing support of planning, budgeting and controlling processes through advanced analytics and AI solutions, powerful data management and data integration are an indispensable prerequisite.

Forecasting 58

Forecasting Predictive Analytics Sales Data Integration 58

AWS Big Data

MAY 18, 2023

It’s even harder when your organization is dealing with silos that impede data access across different data stores. Seamless data integration is a key requirement in a modern data architecture to break down data silos. He is responsible for building software artifacts to help customers. runtime ( 3.5

Testing 75

Testing Data Lake Cost-Benefit Data Integration 75

AWS Big Data

AUGUST 22, 2023

This post proposes an automated solution by using AWS Glue for automating the PostgreSQL data archiving and restoration process, thereby streamlining the entire procedure. He has over 20 years of experience building software and his favorite Amazon leadership principle is “ Leaders are right a lot.”

Data Processing 85

Data Processing Testing Data Lake Data Integration 85

Smarten

AUGUST 17, 2018

As advanced analytics and self-serve, augmented analytical tools make their way into the average enterprise, the average organization struggles to quantify the effects and, moreover, to understand and leverage the changes within the business. But, how do you begin to understand the implications of these changes?

Analytics 40

Analytics Measurement Data-driven Optimization 40

CIO Business Intelligence

JUNE 13, 2022

And the chatbot would be able to understand what you were asking, run analytics on your purchases, and give you a total. In some parts of the world, companies are required to host conversational AI applications and store the related data on self-managed servers rather than subscribing to a cloud-based service. IT Leadership

Data Processing 85

Data Processing Deep Learning Insurance Cost-Benefit 85

Ontotext

AUGUST 22, 2023

The age of Big Data inevitably brought computationally intensive problems to the enterprise. Central to today’s efficient business operations are the activities of data capturing and storage, search, sharing, and data analytics. As a result, organizations have spent untold money and time gathering and integrating data.

Metadata 52

Metadata Knowledge Discovery Big Data Enterprise 52

AWS Big Data

JANUARY 12, 2024

Many organizations, small and large, are working to migrate and modernize their analytics workloads on Amazon Web Services (AWS). We have defined all layers and components of our design in line with the AWS Well-Architected Framework Data Analytics Lens. The data will be consumed by downstream analytical processes.

Data Lake 93

Data Lake Cost-Benefit Visualization Structured Data 93

AWS Big Data

AUGUST 11, 2023

Customers are implementing data and analytics workloads in the AWS Cloud to optimize cost. When implementing data processing workloads in AWS, you have the option to use technologies like Amazon EMR or serverless technologies like AWS Glue. This post is written in collaboration with Elijah Ball from Ontraport.

Data Processing 95

Data Processing Cost-Benefit Optimization Interactive 95

CIO Business Intelligence

MAY 18, 2022

The discipline of enterprise architecture (EA) is often criticized for forcing technology choices on business users or producing software analyses no one uses. Small sees a trend toward redeploying staff that formerly worked in standalone teams on technologies such as cloud or data analytics into “project-based pods to address urgent needs.

Enterprise 104

Enterprise Measurement Data-driven Software 104

AWS Big Data

MARCH 14, 2024

The unwavering reliability of Kafka aligns with our commitment to data integrity. The integration of Ruby services with Kafka is streamlined through the Karafka library, acting as a higher-level wrapper. Vaibhav Pandey , a Staff Software Engineer at Broadcom, is a key contributor to the development of cloud computing solutions.

Management 107

Management Insurance Optimization Strategy 107

IBM Big Data Hub

JANUARY 15, 2024

For instance, organizations that are struggling to build their own IT services can assess whether some internal legacy tech should be replaced with technologies from software-as-a-service (SaaS) providers. Digital transformation is an important component of a modern organization’s business operations.

Digital Transformation 77

Digital Transformation Internet of Things IoT Consulting 77

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 95

Analytics Visualization Data Integration Cost-Benefit 95

CIO Business Intelligence

MARCH 16, 2022

But even before the pandemic hit, Dubai-based Aster DM Healthcare was deploying emerging technology — for example, implementing a software-defined network at its Aster Hospitals UAE infrastructure to help manage IoT-connected healthcare devices. CIO Middle East: Data Analytics is key in healthcare. Repeated small things.

Technology 97

Technology Digital Transformation Business Intelligence Data Warehouse 97

CIO Business Intelligence

JUNE 21, 2022

Service solutions that have native case management workflows (like ServiceNow) or native customer data integrations (like Salesforce) already offer this (similar capabilities) as core to their value,” Miller said. Collaboration Software, SaaS, Unified Communications Lack of clarity in product placement.

Management 94

Management Machine Learning Interactive Marketing 94

Jedox

JULY 31, 2018

Now, we will take a deeper look into AI, Machine learning and other trending technologies and the evolution of data analytics from descriptive to prescriptive. Analytic Evolution in Enterprise Performance Management. Advanced analytics responds to next-generation requirements. This is known as prescriptive analytics.

Technology 44

Technology Prescriptive Analytics Machine Learning Business Intelligence 44

AWS Big Data

FEBRUARY 29, 2024

However, enterprise data generated from siloed sources combined with the lack of a data integration strategy creates challenges for provisioning the data for generative AI applications. For detailed implementation guidance, refer to Unstructured data management and governance using AWS AI/ML and analytics services.

Data Governance 95

Data Governance Unstructured Data Metadata Data Lake 95

AWS Big Data

DECEMBER 13, 2023

Traditionally, customers used batch-based approaches for data movement from operational systems to analytical systems. A batch-based approach can introduce latency in data movement and reduce the value of data for analytics. usually a data warehouse) needs to reflect those changes in near real-time.

Data Warehouse 97

Data Warehouse Snapshot Data Processing Management 97

Smarten

APRIL 19, 2024

Gartner recently estimated that the market for AI software will be nearly $134.8 billion, with the market growing by 31.1% in next several years. In a recent survey of C-suite executives, 80% of said they believe AI will transform their organizations, and 64% said it is the most transformational technology in a generation.

Analytics 57

Analytics Predictive Modeling KPI Machine Learning 57

BI-Survey

AUGUST 1, 2019

Providing results for process improvement is the main way to monetize data. Providing analysis results is the most common form of monetizing data. 40 percent of participants employ this type of data monetization, whereby data analytics is involved. Benefits are tangible.

Cost-Benefit 53

Cost-Benefit Reporting Data Quality Data-driven 53

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 Data Warehouse Analytics Data Processing 52

AWS Big Data

MAY 30, 2023

Customers have been using data warehousing solutions to perform their traditional analytics tasks. About the authors Manish Kola is a Data Lab Solutions Architect at AWS, where he works closely with customers across various industries to architect cloud-native solutions for their data analytics and AI needs.

Data Lake 77

Data Lake Data Analytics Analytics Data Processing 77

IBM Big Data Hub

APRIL 15, 2024

Data integration stands as a critical first step in constructing any artificial intelligence (AI) application. While various methods exist for starting this process, organizations accelerate the application development and deployment process through data virtualization.

Analytics 71

Analytics Optimization Data-driven Metrics 71