Type Title Author Comments Última actualización
Entrada de blog Cloud Database Management - How To Do it Right guest 0 Hace 5 años 5 meses
Entrada de blog The Importance of Big Data Disaster Recovery guest 0 Hace 6 años 5 meses
Entrada de blog Popular Agile Testing Metrics and KPIs and How to Use Them guest 0 Hace 6 años 6 meses
Entrada de blog The Story of Big Data on AWS guest 0 Hace 6 años 7 meses
Entrada de blog What is Big Data Marketing and Does it Help Lead Generation? guest 0 Hace 6 años 7 meses
Entrada de blog Visualizing Big Data and the Connection to Responsive Design guest 0 Hace 6 años 8 meses
Entrada de blog Warehousing Your Data in the Cloud with ETL guest 0 Hace 6 años 9 meses
Entrada de blog Does Big Data Analytics Help Sales Development? guest 0 Hace 6 años 9 meses
Entrada de blog How is Marketing Automation Related to Big Data? guest 0 Hace 6 años 9 meses
Entrada de blog Data Warehouse Security Best Practices guest 0 Hace 6 años 10 meses

Publicaciones

  • Using Machine Learning/AI to Boost the Supply Chain: 5 Use Cases

    Industry - AI to boost the Supply ChainThis article will discuss how supply chains are being improved through the use of innovative technologies before highlighting five uses of artificial intelligence and machine learning in supply chains.

    When you finish reading, you’ll understand why many industry analysts have described A.I. technologies as disruptive innovations that have the potential to alter and improve operations across entire supply chains..

  • Open Source for Big Data: An Overview

    Software Open SourceThis article will describe the relevance of open source software and big data before describing five interesting and useful open source big data tools and projects.

    Big data workloads are those that involve the processing, storage, and analysis of large amounts of unstructured data to derive business value from that data. Traditional computing approaches and data processing software weren’t powerful enough to cope with big data, which typically inundates organizational IT systems on a daily basis.

    The widespread adoption of Big Data analytics workloads over the past few years has been driven, in part, by the open source model, which has made frameworks, database programs, and other tools available to use and modify for those who want to delve into these big data workloads..

  • What is Storage Tiering and How Can it Reduce Storage Costs?

    Tiered storageTiered storage is a way of managing data by assigning it to different types of storage devices/media depending on the current value that the underlying information provides. The efficient management of data recognizes that all information provides an intrinsic value from the time it’s created to the time it becomes obsolete and that this value changes over the information lifecycle.

    The typical factor determining the value of information is how frequently you access it, however, policy-based rules can factor a number of other issues to determine information value. For example, old bank transactions, which might have a low value, could suddenly shift in value depending on special circumstances, such as a tax audit. This article discusses some pros, cons, and best practices for tiered storage..

  • The Importance of Big Data Disaster Recovery

    Analytics information big data Disaster recovery is a set of processes, techniques, and tools used to swiftly and smoothly recover vital IT infrastructure and data when an unforeseen event causes an outage.

    The statistics tell the best story about the importance of disaster recovery—98 percent of organizations reported that a single hour of downtime costs over $100,000, while 81 percent indicated that an hour of downtime costs their business over $300,000...

  • What is Big Data Marketing and Does it Help Lead Generation?

    Bigdata marketing and lead generationBig Data marketing refers to the use of high-velocity, voluminous, and variable data to improve a company’s marketing efforts. When people think of the term Big Data, they often make the erroneous assumption that it’s just about the size of the datasets.

    However, Big Data refers to data expanding on two other fronts —velocity and variety..