Big Data has been
swooping the BI and Analytics world for a while now. It’s touted as the better
way of Data Warehousing for Business Intelligence (BI) and Analytics (BA) projects.
It has removed hardware limitations on storage and data processing. Not to
mention, it has broken the barriers of schema and query definitions. All of
these advancements have sprung the industry in a forward direction.
Literally, you can dump any data in any format and start building analytics on the records. We mean any data whether it’s a file, table, object, or in any schema into Hadoop.
1. EE BigDataNOW™ will organize your Big Data repositories no matter the
source
Ok, so everything is
good until you realize all your data is sitting in your Hadoop clusters or Data
Lakes with no way out; how are you supposed to understand or access your data?
Can you even trust the data that is in there? How can you ensure everyone who
needs access has a secure way of retrieving the data? How do you know if the
data is easy to explore and understand for the average user?
Most importantly, how do
you start exposing your Big Data store with API’s that are easy to use and
create? These are some of the questions you are faced with when you want to
make sense of you Big Data repositories.
Stone Bond’s EE BigDataNOW™ helps you achieve the
“last-mile” of your Big Data journey. It helps you organize your Big Data
repositories, whether in a Lake, in the cloud or on-premise, EE helps make
sense of all the data for your end users to access. Users will be able to
browse the data with ease and expose it through APIs. EE BigDataNOW™ lets you organize the chaos and madness that the
data loading individuals uploaded.
2. Everyone is viewing and referencing the same data
For easy access to the
data, Stone Bond provides a Data Virtualization Layer for your Big Data
repository that organizes the data into logic models and APIs. It lets you
provide a mechanism for administrators to build logical views with secure
access to sensitive data. Now everyone is seeing the same data and not
different versions of it. This reduces the confusion by providing a clear set
of Master Data Models and trusted data sets that are sanctioned to have the
accurate data for their needs. It auto-generates APIs for the models on the fly
so users can access the data through SOAP/REST or OData and be able to build
dashboards and run analytics on the data. It also provides a clean queryable SQL
interface, so users are not learning new languages or writing many lines of
code. It finally brings a sense of calmness and sureness that is needed for
true Agile BI development.
3. It’s swift … did we mention you access & federate your data in
real-time?
EE BigDataNOW™ can be a valuable component on the ingestion
side of the Big Data store too; it will federate, apply transformations and
organize the data to be loaded into the Data Lake using its unique Agile ETL
capabilities, making your overall Big Data experience responsive from end to
end. EE BigDataNOW™ has a fully UI
driven, data workflow engine that loads data into Hadoop whether its source is
streaming data or stored data. It can federate real-time data with historical data on demand for better analysis.
One of the major
complexities that Big-Data developers run into is building and executing the
Map-Reduce jobs as part of the data workflow. EE BigDataNOW™ can create and execute Map-Reduce jobs through its
Agile ETL Data Workflow Nodes; this will help run Map-Reduce jobs and store results
in a meaningful, easy way for end users to be able to access the Map-Reduce
jobs.
5. EE BigDataNOW™ talks to your other non-Hadoop Big Data sources
EE BigDataNOW™ includes non-Hadoop sources such as Google Big
Query, Amazon Redshift, SAP HANA, etc. EE
BigDataNOW™ can also connect to these nontraditional Big Data sources, and populate
or federate data from these sources for all your Big Data needs.
To read more about Big Data, don’t forget to check out Stone Bond’s Big Data page. What are you waiting for? Break through your Big Data barriers today!
This is a guest blog post written by,
To read more about Big Data, don’t forget to check out Stone Bond’s Big Data page. What are you waiting for? Break through your Big Data barriers today!
This is a guest blog post written by,
