Un gran estudio de más de 40 páginas por parte de Philip Russom, que puedes descargar gratuitamente desde aquí
Os dejo a continuación, un resumen de los contenidos y algunos de los principales hallazgos del estudio. Muy interesante.
Para saber más de Data Lakes:
Diferencias entre Data Lake y Data Warehouse
Let’s briefly take a look at each one: Data. A data warehouse only stores data that has been modeled/structured, while a data lake is no respecter of data. It stores it all—structured, semi-structured, and unstructured. [See my big data is not new graphic. The data warehouse can only store the orange data, while the data lake can store all the orange and blue data.] Processing. Before we can load data into a data warehouse, we first...
Sabes quién creó el término 'Data Lake'?
What is a data lake? A data lake is a repository designed to store large amounts of data in native form. This data can be structured, semi-structured or unstructured, and include tables, text files, system logs, and more. The term was coined by James Dixon, CTO of Pentaho, a business intelligence software company, and was meant to evoke a large reservoir into which vast amounts of data can be poured. Business users of all kinds can dip into...
Predictions: A Cynic’s Guide To BI In 2017
Genial esta descripción de Timo Elliot (uno de los mayores especialistas en Business Intelligence). No tiene desperdicio!! Businesspeople Businesspeople will be dissatisfied with their BI systems (this is “Timo’s First Law of BI”) Executives will refuse to learn to use any other data tool than Excel (and not even the newer features of that). No matter how good the BI system, businesspeople will make bad decisions based on gut feel. Executives...
Talend Big Data
Download whitepaper An enterprise data lake provides the following core benefits to an enterprise: New efficiencies For data architecture through a significantly lower cost of storage, and through optimization of data processing workloads such as datatransformation and integration. New opportunities For business through flexible “schema-on-read” access to all enterprise data, and through multi-use and multi-workload data processing on...
OLAP for Big Data. It´s possible?
Hadoop is a great platform for storing a lot of data, but running OLAP is usually done on smaller datasets in legacy and traditional proprietary platforms. OLAP workloads are beginning to migrate to the one data lake that is running Hadoop and Spark. Fortunately, there are a number of Apache projects that are starting to make OLAP possible on Hadoop. Apache Kylin For an introduction to this interesting Hadoop project, check...
Big Data, casos, tecnologias y aplicaciones reales
Os mostramos a continuación, una buena selección de ejemplos, tecnologías y casos aplicables de Big Data usando las principales tecnologías, con enfoque Data Lake, de la mano de los especialistas de stratebi ...
