Clearlake Capital to Acquire Global Cybersecurity, Data Intelligence and IT Operations Management Software Leader Quest from Francisco Partners

Quest | November 29, 2021

Data Intelligence
Quest Software , a global cybersecurity, data intelligence, and IT operations management software provider, announced it signed a definitive agreement with Clearlake Capital Group, L.P. (together with certain of its affiliates, “Clearlake”) to acquire the Company from Francisco Partners. Patrick Nichols, current CEO of Quest, will continue to lead the Company supported by the existing executive management team. Upon closing of the transaction, Clearlake will become the majority shareholder in Quest. The terms of the transaction were not disclosed.

“We have long admired Quest as a leading identity-centric cybersecurity, data intelligence, and IT operations management software platform and the Company’s software solutions that help secure enterprise IT environments,” said Behdad Eghbali, Co-Founder and Managing Partner at Clearlake. “We are excited to partner with Patrick and Carolyn McCarthy, Quest’s CFO, to utilize Clearlake’s O.P.S.® framework to help the Company strengthen its strategic growth plans including best practices to accelerate cloud/SaaS adoption and support its buy-and-build strategy.”

"IT teams worldwide rely on Quest to help them solve critical challenges that enable business growth and address crucial strategic initiatives. Quest has evolved to become a market leader in identity-centric cybersecurity, data intelligence, and IT operations management and I want to thank Francisco Partners for helping Quest realize this vision. Our new partnership with Clearlake will accelerate Quest's momentum as a leader and innovator as we increase our investment pace in our core product roadmaps, cloud/SaaS offerings, and global presence. We will continue to expand our customer base as computing environments and related management, modernization, and security challenges, become more complex.”

Patrick Nichols, CEO of Quest

“We are proud of the tremendous progress Quest has made since re-launching as an independent company, and I want to recognize Patrick Nichols and the management team for strong execution,” said Dipanjan “DJ” Deb, Co-Founder and CEO of Francisco Partners. “We have a long and successful track record executing divisional carve-out transactions and are grateful to have had the opportunity to work with the Quest team to create value for the company, its customers, and its partners. We wish the Quest organization well in their new partnership with Clearlake.”

Founded in 1987, Quest Software has built a reputation over three decades as a critical software solution provider for security-sensitive customers and a leader of innovation addressing rapidly evolving risks and security threats. Quest enables today's edgeless IT ecosystem – across people, applications, and data to endpoints – allowing customers to maintain controls, mitigate and contain security threats proactively, and maintain operational up-time while decreasing costs.

Quest's key business segments include:
  • One Identity and OneLogin, making Quest the only identity-centric cybersecurity software vendor providing industry-recognized leading solutions across all aspects of a unified identity security and management approach crucial to taming identity sprawl and addressing identity-based attacks.
  • Platform Management for Microsoft®, which provides software for IT operations resilience and flexibility while enabling organizations to stay in control by securing and managing Active Directory.
  • Information Management and erwin by Quest, a pioneer and leading provider of data operations and intelligence software solutions that modernize infrastructure, optimize performance and deliver applications faster, with offerings including Toad for Oracle®, erwin Data Modeler, erwin Data Intelligence, Foglight, ApexSQL and SharePlex®.
  • Data protection and endpoint management software solutions to control data growth and optimize system availability with NetVault, QoreStore, and Kace® offerings.

“It has been a pleasure partnering with Patrick and the entire management team at Quest in scaling the business both organically and through strategic acquisitions,” said Brian Decker, Partner and Christine Wang, Principal at Francisco Partners. “Since our partnership with the Company, Quest has evolved to become an innovative leader in the cybersecurity, data intelligence and IT operations management markets delivering significant value to its customers and partners.”

“With a robust portfolio of market-leading software and SaaS solutions alongside a rich history of product innovation, we believe Quest is well positioned to capitalize on emerging growth trends in identity-centric cybersecurity, data intelligence and IT operations management software markets,” said Prashant Mehrotra, Partner, and Paul Huber, Principal at Clearlake. “Now with significant scale and completely independent, Quest is strategically differentiated in the market as a buy-and-build platform and industry consolidator, and we’re thrilled to partner with Patrick, Carolyn and the management team to help Quest accelerate growth organically and through M&A.”

The transaction is expected to close in the first quarter of 2022, pending customary regulatory approvals and closing conditions. Goldman Sachs acted as sole lead financial advisor to Quest. J.P. Morgan also acted as financial advisor and Paul Hastings LLP acted as legal advisor to Quest.

Silicon Valley Tech Investment Bank and Morgan Stanley along with BoA Securities, Barclays, Evercore, and William Blair acted as financial advisors to Clearlake. Sidley Austin LLP acted as legal advisor to Clearlake.

Goldman Sachs, Morgan Stanley, BoA Securities, Barclays, Credit Suisse, BMO Capital Markets and Citigroup provided committed debt financing for the transaction.

About Quest
Quest creates software solutions that make the benefits of new technology real in an increasingly complex IT landscape. Quest helps customers solve their next IT challenge, from database and systems management to Active Directory and Office 365 management and cybersecurity resilience. Around the globe, managing over 250 million identities, more than 100,000 customers, 15,000 partners and 97 of the Fortune 100 count on Quest to deliver proactive management and monitoring for the next enterprise initiative, find the next solution for complex Microsoft challenges, and stay ahead of the next threat.

About Clearlake
Clearlake Capital Group, L.P. is an investment firm founded in 2006 operating integrated businesses across private equity, credit and other related strategies. With a sector-focused approach, the firm seeks to partner with experienced management teams by providing patient, long-term capital to dynamic businesses that can benefit from Clearlake’s operational improvement approach, O.P.S.® The firm’s core target sectors are technology, industrials and consumer. Clearlake currently has approximately $55 billion of assets under management and its senior investment principals have led or co-led over 300 investments. The firm has offices in Santa Monica and Dallas.

About Francisco Partners
Francisco Partners is a leading global investment firm that specializes in partnering with technology and technology-enabled businesses. Since its launch over 20 years ago, Francisco Partners has invested in more than 300 technology companies, making it one of the most active and longstanding investors in the technology industry. With more than $30 billion in assets under management, the firm invests in opportunities where its deep sectoral knowledge and operational expertise can help companies realize their full potential.


These two attributes lead us to naturally gravitate towards sharing some of the best reads we come across. You can think of this infographic as an ideal list of books to have in bookshelf of every data scientist / analyst. These books cover a wide range of topics and perspective (not only technical knowledge), which should help you become a well rounded data scientist.For your convenience, we have categorized this bookshelf in following categories: Analytics, Data Science, Data Visualization and Web Analytics. The ones classified under category “Analytics” are actually books which help you understand the perspective of data based decisioning.


These two attributes lead us to naturally gravitate towards sharing some of the best reads we come across. You can think of this infographic as an ideal list of books to have in bookshelf of every data scientist / analyst. These books cover a wide range of topics and perspective (not only technical knowledge), which should help you become a well rounded data scientist.For your convenience, we have categorized this bookshelf in following categories: Analytics, Data Science, Data Visualization and Web Analytics. The ones classified under category “Analytics” are actually books which help you understand the perspective of data based decisioning.

Related News


Immuta Integrates with Snowflake’s Data Lineage

Immuta | June 15, 2022

Immuta, the market leader in data access and data security, announces an expanded partnership with Snowflake, the Data Cloud company, allowing Immuta customers to use Snowflake's data lineage feature to automatically propagate data classification tags across the data lifecycle, removing manual tagging and making it easier and simpler for customers to enact data policies. Immuta is one of the first partners to use Snowflake's data lineage solution to increase consumer confidence through improved data security and uniform policy enforcement. “Data is power in our modern business landscape due to its ability to improve insights and drive competitive decision-making for companies. But, today’s complex data environment makes it challenging for organizations to quickly identify and derive value from their data, while also managing data security and access. Mapping and tagging data through data lineage is a critical piece to this data management puzzle, and we’re thrilled to be partnering with Snowflake on this initiative as part of our continued support of their cloud data management vision.” Steve Touw, CTO, Immuta Growing digitization, worldwide privacy standards, and a remote workforce have resulted in an explosion of data, data users, and policy. Therefore, today's enterprises confront worldwide data access control and data security concerns, making policy enforcement at scale challenging to administer. Data lineage — the act of mapping and categorizing data based on its provenance and where it flows so that policy can follow – assists companies in better managing these data security and access requirements. Tarik Dwiek, Senior Director of Technology Alliances at Snowflake said that “Customers rely on Snowflake to help maximize the value of their data. But in order to accomplish this, organizations must have insights into what their data is, where it came from and where it is going. Our new data lineage capabilities can provide customers with access to faster and safer data analytics, while Immuta’s data access and security capabilities help ensure that the right people can access the right data at the right time.” Understanding data lineage is becoming more critical for data quality and governance. The issue is that crucial information linked with data lineage is often lost during data migration and transformation. Snowflake's new data lineage capabilities aids in the tracking of needed information, and with the Immuta connection, will be able to automatically disseminate the tagging required for data policy enforcement with no human coding. Therefore, data teams may extract more value from their data while still preserving their data assets and complying with privacy requirements.

Read More


Prophecy Accelerates Adoption of Lakehouse Technology

Prophecy | June 22, 2022

Prophecy, the premier low-code platform for data engineering, today announced the release of Prophecy for Databricks, a powerful new service that enables building data pipelines for business intelligence and machine learning simpler and quicker. With a visual drag-and-drop canvas, this platform allows anybody interested in data engineering to visually and interactively create, deploy, and monitor data pipelines on Apache Spark. Prophecy for Databricks, designed for usage by both seasoned data engineering teams and non-programmer data citizens, allows several more people to simply develop pipelines, transfer them to production, and expedite the transformation of enterprises to become data-driven. With 10x users enabled, data teams see a dramatic improvement in operational efficiency and data quality, allowing them to manage more pipelines than ever before. According to IDC, data is being created at a 23% annual growth rate, which means that 181 zettabytes of data will be developed by 2025. Businesses are struggling to keep up with the rate at which data is growing. According to Gartner, the DBMS market is nearly $80 billion and has grown 22% in the last year, with cloud DBMS rising even faster than the overall DBMS market. Existing data engineering products do not address the requirements of businesses and have proven to be overly complex and inefficient. Businesses can 10x data engineering with Prophecy for Databricks, resulting in dramatic increases in data practitioners' doing data engineering, individual productivity, data pipeline reliability, and data quality. "The industry need for data & analytics far outstrips what can be produced by data engineers programming in notebooks. With this release of Prophecy for Databricks, we're providing powerful, visual tools that enable an order of magnitude more data users to quickly develop data pipelines, at the same level as programmers. This expansion of data engineering to non-programmers is the only way to realize the potential of data at scale." Raj Bains, CEO and co-founder of Prophecy

Read More


Ontotext's GraphDB 10 Brings Modern Data Architectures to the Mainstream with Better Resilience and Еаsier Operations

Ontotext | July 05, 2022

With the ever-growing complexity of enterprise data, it's paramount for organizations to have efficient, dependable and cost-effective tools to let them connect the dots of their enterprise knowledge. Over the past 10 years the knowledge graph paradigm has matured and has won its position at the core of the next generation data management and content management systems. Ontotext's GraphDB is the leading database engine for managing knowledge graphs, powering business critical systems in many of the biggest enterprises across various industry verticals. These enterprises choose GraphDB, because it is cloud agnostic and offers predictable performance across a wide range of workloads, architectures and infrastructures. "In GraphDB 10 we did a lot to make the most advanced data management technology as robust and easy to operate as it must be in order to penetrate the mainstream market." Atanas Kiryakov, CEO of Ontotext GraphDB 10.0 is the first major release since GraphDB 9.0 was released in September 2019. It implements next generation, simpler and more reliable cluster architecture to deliver even better resilience with reduced infrastructure costs. GraphDB 10 lowers the complexity of operations with better automation interfaces and a self-organized cluster for automated recovery. Deployment and packaging optimizations allow for effortless upgrades across the different editions of the engine, all the way from GraphDB Free to the Enterprise Edition. The improved full-text search (FTS) connectors of GraphDB 10 enable more comprehensive filtering as well as easier downstream data replication. Finally, parallelization of the path search algorithms brings massive improvement in graph analytics workloads through better exploitation of multi-core hardware. New high-availability cluster with enhanced resilience, easier and cheaper operations GraphDB 10 introduces a high-availability cluster architecture, based on the Raft consensus algorithm. Now any node can be either a leader or a follower, where the leader is like the master node in the old cluster and the followers are similar to the worker nodes. Unlike the old cluster, now every node contains a replica of the data – there is no dedicated master node that only distributes, but does not process queries. The Raft consensus algorithm uses majority voting to determine the current leader, and consensus to confirm every write operation. This ensures a high uptime, zero data loss, fault tolerance and smooth recovery from failures. While the old cluster had to be defined at the repository level, the new cluster is defined for the entire GraphDB instance. This means that every created repository automatically becomes part of the cluster. The new cluster also handles transactions differently – very similarly to non-cluster environments. This unlocks new use-cases, such as using the Sequences plug-in, which were not possible with the old cluster. As a result of all these changes, the new cluster architecture lowers the operational costs. It minimizes the hosting expenses by removing the master nodes, makes it easier to automate with the new cluster API and eliminates the need to configure complex third party software. Effortless upgrade path as your business develops Unlike previous versions, GraphDB 10 is packaged as a single distribution that can run in Free, Standard or Enterprise Edition modes depending on the currently set license. It requires zero development effort to pass from one edition to another. GraphDB 10 also makes it easy to unlock new features as one needs them (such as concurrency, high-availability, down-stream replication, etc.) or to replace bespoke features with generic software configurations. The single GraphDB distribution requires at least Java 11. It is also possible to export a repository with an expired license so users are never locked out of their own data. Improved search and downstream replication experience GraphDB 10 offers improved FTS connectors with even more powerful property value and document filtering capabilities. The connectors can now perform very fine-tuned filtering at every level of the indexing process. The new release also features a two-variable comparison to cover numerous new use-cases, which were not possible before. Faster analytics with new parallelization capabilities Last but not least, GraphDB 10 ensures that users get the optimal performance for the number of cores they have purchased. The improved graph path search algorithm can run in parallel mode so that complex path searches run 5 to 10 times faster than before. This is just one of the optimizations to enable customers with a larger number of cores not only to handle a big count of concurrent requests but also to get faster processing of a single complex query. And much more There are many other changes and improvements in the new release, including: Removing OntoRefine from GraphDB and developing it as a separate product. All existing OntoRefine and RDF mapping functionalities will be available in it. Retouching GraphDB Workbench to make it even easier to use and introducing a French translation of the UI. Simplifying remote locations, which now serve mainly as a facility for easier cluster management. Remote locations in GraphDB 10.0 cannot be activated but the repositories from them are accessible from the workbench together with the local repositories. Introducing Java 11 as a minimum requirement in RDF4J, just like GraphDB 10.0. It includes numerous fixes and improvements of the overall performance. Upcoming improvements With the release of GraphDB 10.0 Ontotext did the heavy lifting to deliver numerous improvements in the architecture, infrastructure and packaging that all together deliver a new level of reliability and make deployment, application development and system operations simpler, easier and more cost effective. It lays down a stong foundation for many other improvements coming soon in the next minor releases. Two major areas of improvement in 10.1 will be query performance optimization and availability on some of the major cloud platforms. About Ontotext Ontotext is a global leader in enterprise knowledge graph technology and semantic database engines. Ontotext employs big knowledge graphs to enable unified data access and cognitive analytics via text mining and integration of data across multiple sources. Ontotext GraphDB engine and Ontotext Platform power business-critical systems in the biggest financial services, publishing, healthcare, pharma, manufacturing companies and public sectors.

Read More