Blazent IT Data Intelligence Technology:

Transcription

1 Blazent IT Data Intelligence Technology: From Disparate Data Sources to Tangible Business Value White Paper

2 The phrase garbage in, garbage out (GIGO) has been used by computer scientists since the earliest days of computing. Originally, it was a reminder about programming accuracy. But in today s data-swamped era, the phrase gets at the very heart of enterprise IT operations. All business decisions rely on data, and in modern enterprises, everything is data. But as that data increases in volume and variety, and the IT environment becomes increasingly more complex, the quality of that data is constantly called into question. In fact, a recent Gartner report revealed that in enterprises today, poor data quality is the primary reason for 40% of all data initiatives failing to achieve their targeted benefits. The implications of inaccurate, incomplete, overlapping, colliding, or otherwise poor data are dire CIOs and their IT teams face mounting expectations to provide the data needed to make sound business decisions. But with current CMDB (configuration management database) and service management tools, those expectations are impossible to achieve. Data gushes in from disparate sources. There s increasing pressure for accurate, immediate action. Yet confidence in the actual quality and reliability of that data is lacking, both in the CIO office and in IT operations. The implications of inaccurate, incomplete, overlapping, colliding, or otherwise poor data are dire, ranging from inability to enforce SLAs and overpaying for software licenses and other services, to reduced productivity and IT outages. A severe outage in a typical Fortune 50 enterprise might cost up to $60 million each minute. And all the losses, large and small, end up being absorbed by the enterprise as a cost of doing business. Blazent has developed the first data intelligence solution built from the ground up to assess, verify, and certify the quality of IT data, of any volume, velocity, or variety. Blazent not only takes in a greater breadth of data than any other approach, it also provides near-real-time analytics on all the data ingested as well as providing contextual history across enterprise environments and across time. This paper provides an overview of Blazent s IT data intelligence technology, which harnesses and works with the widest range of IT data sources, providing business benefit in four use cases: data quality management, data governance, operational validations, and software inventory analysis. White Paper IT Data Intelligence: From Disparate Data Sources to Tangible Business Value 2

3 Inside The Blazent Solution Data Quality Management Data Governance Operational Validations Software Inventory Analysis Blazent Data Intelligence Platform Data Evolution Blazent Big Data Engine The Blazent IT data intelligence technology can capture any relevant data from any source, in near time, then process it, purify it, and make it available for accurate analysis and insight. Application Financial Performance Dev Ops Distribution Data Center Management Event Management Anti Virus Spreadsheets Software Problem Management Server Monitoring Contract Management MSPs Virtualization Application Depen dency Configuration Incident Purchasing Marshaling IT Data Across Disparate Sources Change Management External Cloud Asset Management Discovery Human Resources Security Blazent has been in the data quality business for more than a decade. Over that time, the company has not only refined its algorithms, it has also gained experience with many different IT data sources across diverse industries<link to the Blazent Experience Across IT Data Sources paper>. The result is the industry s most complete, accurate, and trusted data set. This accumulated experience is what powers Blazent s data intelligence solutions. Blazent works with data containing information about people, physical and virtual assets, finances, datacenters, end-user computing devices, clusters, external and private clouds, tool stacks, networking, application performance, and more. The Blazent IT data intelligence technology can capture any relevant data from any source, in near time, then process it, purify it, and make it available for accurate analysis and insight. Blazent s unique combination of quantity and diversity of data sources lets it determine what s true, accurate, and complete. Blazent Big Data Engine Applies Data Intelligence Technology Blazent has built a big data processing cluster able to work with all the disparate data sources it encounters, then to store every representation of every entity of every source of all that data, across time. Data is fed into the Blazent Big Data Engine, which is hosted in cloud environments including Amazon Web Services (AWS) in North America and Europe and the Verizon Terramark secure cloud infrastructure. To optimize flexibility, the Blazent architecture incorporates a number of leading open-source White Paper IT Data Intelligence: From Disparate Data Sources to Tangible Business Value 3

4 tools. For example, the Blazent engine leverages the best of the Apache Hadoop software framework for distributed storage and processing, plus the best of the Apache Cassandra distributed database management system (DBMS). Both these open-source tools are designed to handle very large data sets across multiple clusters, using commodity server hardware. Data is spread across the Cassandra DBMS. The Blazent engine takes advantage of the Redis key-pair value dictionary, enabling recognition of whether a particular entity or piece of data has been seen before, or if anything about it has changed since the last time it was encountered. The Data Evolution Process Historicity Purification Relationship Analysis Identity Management Data Atomization Messaging from the various nodes of the cluster is via the Apache ActiveMQ message broker. The Blazent Big Data Engine s processing structure uses the ultrafast Spark query engine, the leading query engine for NoSQL databases. It also uses Spark s scalable MLlib (Machine Learning Library) of common learning algorithms and utilities. Blazent uses HDFS (Hadoop Distributed File System) for reliable storage of its massive datasets. Hadoop and the HDFS structure enable long-term history of all the data the Blazent engine processes. In this way, enterprises can draw from the accumulated data and knowledge gained from that data to make better decisions. Additionally, the data remains available for future analysis. The Big Data Engine sits at the intersection of all Blazent s aligned and validated data across a large swath of the IT world, providing insight into what s happening, who s involved, what s working as it should, and where more attention should be focused. Use Case: Data Quality Management Blazent IT data intelligence technology goes beyond a simple service management platform, providing the configuration management services needed to manage all aspects of IT data quality, including every CI (configuration item) in the CMDB and its sources, roles, operations, and dependencies. After taking in data from multiple sources, the Blazent engine then uses patent-pending Data Atomization technology to break the data into its smallest parts, then purifies, normalizes, and aligns it. Blazent technology performs identity management, relationship analysis, and purification of each CI, including analytics on each CI s attributes, relationships, and status. All the historical artifacts are stored, securely and for the long term. White Paper IT Data Intelligence: From Disparate Data Sources to Tangible Business Value 4

5 Utilizing the output of this rigorous atomization process, the Blazent technology compares the truth of each CI within the values of the service management platform. The result is the most accurate data quality management process available today. Use Case: Data Governance Effective data governance depends on trusted, validated data quality. Blazent technology provides the data-quality disciplines that enable true asset management, to achieve data governance goals such as: Lifecycle analysis Verification of the accuracy of billing by MSPs and other service providers Visibility into general ledger account codes Insight into key governance attributes, such as owned by, managed by, and supported by Use Case: Operational Validations High-quality data is a necessary first step for measuring internal and external operational SLAs, including the number of end-user devices in an enterprise and what percentage of them have the latest version of antivirus software installed and running. Blazent can pinpoint areas of operational risk, such as assets lacking proper encryption, or devices or users lacking a resource they are supposed to have. Blazent can show operational tool coverage: what s running and over which enterprise environments, both virtual and physical. Use Case: Software Inventory Analysis Managing software inventory is a specialized use case of overall IT data management that has enormous cost, productivity, and security implications. The Blazent technology reveals gaps in software inventory, as well as where the enterprise is running multiple versions of the same software. It also shows actual software usage throughout the enterprise: i.e., not only where software is installed, but whether it is being used as intended. Using the insights gained through Blazent s software inventory analysis, enterprises can reduce software maintenance costs, avoid redundant licensing charges, rationalize software across the environment, and make sure that the right software, in the right version, is in place and accessible to the people who need it. White Paper IT Data Intelligence: From Disparate Data Sources to Tangible Business Value 5

6 Conclusion IT decisions are only as good as the data used to make them. The Blazent IT data intelligence platform is the first solution purpose-built for the language and business of IT. With Blazent s IT data intelligence technology, enterprises are able to: Identify and organize IT data from all possible sources Ensure the accuracy and consistency of all the data Perform near-time analytics on all the data Store all the data securely and for the long term Provide contextual history that makes possible an extra dimension of analysis: across time Enable the data to be used to improve tangible use cases including data quality management, data governance, operational validations, and software inventory analysis Intelligent, actionable data: It s the key to reducing costs, controlling complexity, and improving service levels. That s the Blazent advantage. About Blazent 1633 Bayshore Hwy Suite 341 Burlingame, CA Blazent is the leader in IT data intelligence. The Blazent Data Intelligence Platform is powered by the company s big data engine and patented, 5-step Data Evolution Process. It transforms and validates all IT data, enabling enterprises and managed service providers to make business decisions based upon complete and accurate data. Blazent is headquartered in Silicon Valley. For more information, visit or follow us on 2015 Blazent, Inc. All rights reserved. Blazent, the Blazent logo and Data Intelligence. Redefined are trademarks of Blazent, Inc. all other company and product names mentioned herein may be trademarks of their respective owners. ITDI-WP 0615 White Paper IT Data Intelligence: From Disparate Data Sources to Tangible Business Value 6