Starting in 1996, Alexa Internet has been donating their crawl data to the Internet Archive. Flowing in every day, these data are added to the Wayback Machine after an embargo period.
Starting in 1996, Alexa Internet has been donating their crawl data to the Internet Archive. Flowing in every day, these data are added to the Wayback Machine after an embargo period.
TIMESTAMPS
The Wayback Machine - https://web.archive.org/web/20180217141025/http://www.datawerks.com:80/
Data Virtualization and data mashups.
Mashup data from any number of sources in real-time with high performance. Data correlation, analytics and profiling help to identify patterns and links between sources.
Unlimited Sources of any format.
Mashup any number and all types of sources including structured, unstructured, web and big data. Patent-pending technology accesses data without performance impacts.
Real-Time.
Analyze information the moment they are being created and with response times that have never been seen before.
No ETL. No Data Replication.
Virtually unify disparate data sources. No more ETL or data replication! Query all sources as though they belong to one big source.
Half the time. Half the cost.
Quickly deliver integrated data and insights to meet changing business needs. Flexible data delivery options include web services, reports, triggers and alerts.
OUR TECHNOLOGY
dataWerks has pioneered an innovative data virtualization solution that offers a radically new approach to delivering real time business insights. The concepts behind the core product ‘dataWerks’ were conceived in 2012 and filed for patent in 2013.
dataWerks enables real time
data virtualization and enterprise
data mashup without data
replication. It reads and analyzes
data from multiple sources, including
structured, unstructured,
big data and social media within
milliseconds.
Integrated insights
can be quickly generated and
delivered via multiple channels
at half the cost and half the
time when compared to legacy data
warehousing technology.
dataWerks‘ proprietary technology
reuses the principles of a
book index. It stores the References
to the actual information
and keeps them up-to-date in
real time, without adding any
overhead to the source systems.
All operations, aggregations
and analysis can be done on
those References without
touching the underlying
sources again. This takes out the
complexity of federating queries
across multiple systems and
formats or transforming them
into a unified format.
This is the fourth article in the larger series of interviews around diverse aspects of Data Science technology and its practical implementation in modern businesses. Today in the interview: [...]
This is the third article in the larger series of interviews around diverse aspects of Data Science technology and its practical implementation in modern businesses. Today in the interview: Paulo [...]
