Despite all of the big data hype and an ever-emerging slew of analytics tools, enterprises are leveraging only a fraction of the information that’s available. Much of the data is trapped in silos — everything from disparate on-premises systems to myriad cloud applications.
Add other data feeds into the mix from social, mobile and the Internet of Things (IoT) and the volume of data spikes to more than we can fathom.
But bringing the right feeds together quickly for real-time analysis is difficult and time consuming — primarily because enterprises are relying on outdated ETL (extract, load and transform) tools or on hand-coding connectors to transform data for analysis.
SnapLogic, a San Mateo Calif.-based enterprise Integration Platform as a Service (iPaaS) provider, claims the Summer 2016 release of its SnapLogic Elastic Integration Platform can solve the problem by helping customers aimed at to help them ingest any kind of data from anywhere at any time.
SnapLogic 'Enables the Data Era'
Darren Cunningham, vice president of marketing at SnapLogic, said his company is "enabling the modern data era" with its pre-built data connectors called Snaps. Some connect clouds from providers like Salesforce, Workday, and ServiceNow. Others bring data in from legacy on premise applications, data lakes and more.
The Summer 2016 release brings new additions to SnapLogic’s library of more than 400 of these intelligent connectors, and enhances the core platform with improved performance and new data governance features for hybrid deployments.
"Data isn't always neatly stored in columns and rows," Cunningham told CMSWire. To compete today, companies must include unstructured and semi-structured data needs to be included in analytical efforts, he added. Part of the beauty of SnapLogic's approach is that end users don't have to leave the applications they are working in to leverage the data-driven insights, he explained.
SnapLogic Adds, Updates Multiple Snaps
In a major new release, SnapLogic introduced several new Snaps and updated others. The release includes:
- A new Snap for the Apache Hive data warehouse, which automates execution of Data Manipulation Language (DML) and Data Definition Language (DDL) statements for rapid queries on either Cloudera- or Hortonworks-based Hadoop clusters
- A new Snap that connects a Teradata database as part of an integrated data pipeline for enhanced business analytics
- Enhanced encryption for the SnapLogic Hadooplex — the data processing engine that is deployed on a Hadoop cluster — that allows cloud service and database credentials to be stored and encrypted under the customer’s control without leaving the SnapLogic environment, bringing more flexibility and security to data processing in Hadoop clusters
- An enhanced Mapper Snap, which makes it faster and simpler to search, filter and map the thousands of entries in complex schema trees from applications such as Salesforce, SAP and NetSuite
- Enhancements to the Snap for the Anaplan project planning platform to support handling of input errors to aid in data governance
- An updated Tableau Snap, which lets users write, format and extract data from the current version of Tableau for advanced business analytics
- Updates to Snaps for Google BigQuery, Google Analytics and NetSuite to improve performance
SnapLogic also enhanced its platform's governance by adding features for traceability and auditability, which includes capturing and logging pipeline parameters, restricting triggered tasks to a single instance execution, whitelisting IP ranges for cloud triggered executions and more.
There's little question that legacy providers like Informatica (where SnapLogic CEO Gaurav Dillon, SnapLogic CTO James Markarian, SnapLogic VP of Engineering Vaikom Krishnan, and Cunningham all used to work) and Tibco claim to help their customers get the same kind of work done successfully.
According to Gartner's latest iPaaS Magic Quadrant, Informatica, Dell Boomi, MuleSoft, Snaplogic and Jitterbit are all Leaders. But SnapLogic stands out with its "rich and differentiating features for analytics and big data integration," which are becoming increasingly important in the digital age.