Big Data. It’s proliferating companies like never before. Yet these high volumes of data are often found in pockets and silos throughout the organization without a truly comprehensive way to transform the data into the actionable insights that can deliver real value.
To efficiently leverage data so that it can provide visibility into meaningful information consider a Big Data search and analytics platform that delivers these five critical elements:
- Natural Language and Multi-Language Understanding. For a search and analytics solution to be effective, it needs to understand the natural language as it’s spoken across ever major language. If it can “speak” the way we do, it will better understand the data it’s analyzing, especially when searching unstructured content such as email and document files. It should also feature machine learning algorithms so that it can learn as it progresses, delivering more value with each new volume its analyzes.
- Extensive Connections for Comprehensive Indexing. To make the most of the multiple pockets of data throughout the organization, a search and analytics solution needs to have a wide range of connectors so that it can support every type of data, making it easily ingested into the platform so that it’s included in a comprehensive analysis. From databases and enterprise applications including CRM systems such as SAP, to cloud applications like Office 365, GoogleApps and Salesforce and cloud storage such as Box and Microsoft Onedrive, having a connector for every vital application in the business will ensure that the resulting insights deliver a complete view into the business.
- Support for the Structured and Unstructured. When analyzing business data, it’s critical to include unstructured data, such as email and document files, as well as structured content, like the data included in databases. Only when both are included in an analysis can true insights be revealed. Since so much valuable data is embedded in unstructured files, evaluating these contents can produce truly insightful information into the business that can’t otherwise be recognized by evaluating structured forms of content.
- Extensive Security and Access Control. In many applications, data is not only a critical asset, it’s also private and regulated. Any solution that touches regulated data must follow strict security and compliance guidelines, ensuring that policy controls are in place. Be sure to select a search and analytics platform that supports stringent access controls, including user authentication, cross-domain security and secure communications, to assure that compliance practices are followed.
- Agility to Support Hybrid Infrastructure. The cloud is quickly changing everything. When large data sets are in play, it’s very likely that much of that data is being retained in cloud-based environments. Whether retained in public cloud solutions, such as Amazon Web Services (AWS), or private cloud architectures, data still must be accessed and integrated into a comprehensive enterprise search and analytics solution to be part of a successful solution for true business insights. Here it’s critical to select a solution that will not only support any combination of a private and public cloud infrastructure as well as on-premise architectures with a hybrid approach to data analysis that will also support hundreds of millions of documents and billions of database records. This will ensure that regardless of how large the environment becomes, and wherever data may reside, it can become part of a comprehensive analysis for true and accurate results.
Big Data can produce Big Insights, yet only when organizations take a holistic approach to enterprise search and analytics so that every pocket and silo data of its data assets are included in the analysis project. When a comprehensive approach is taken, the insights can be exceptionally revealing, producing value beyond any expectation and transforming data into a true competitive advantage.
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Written by: Laurent Fanichet, vice president of marketing for Sinequa.
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