ADAudit Plus helps keep your Windows Server ecosystem secure and compliant by providing full visibility into all activities. ADAudit Plus provides a clear picture of all changes made to your AD resources including AD objects and their attributes, group policy, and more. AD auditing helps detect and respond to insider threat, privilege misuse, and other indicators of compromise, and in short, strengthens your organization's security posture. Gain granular visibility into everything that resides in AD, including objects such as users, computers, groups, OUs, GPOs, schema, and sites, along with their attributes. Audit user management actions including creation, deletion, password resets, and permission changes, along with details on who did what, when, and from where. Keep track of when users are added or removed from security and distribution groups to ensure that users have the bare minimum privileges.
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CallTrackingMetrics is the only SaaS platform that uses call tracking and conversion intelligence to inform contact center automation—resulting in a more personalized customer experience. Discover which marketing campaigns are generating leads and conversions, and use that data to automate call flows and power your contact center. Unify communications across your entire organization with our phone, text, online form, and live chat tools. More than 100,000 users around the globe trust CallTrackingMetrics to manage communications for their marketing, sales, and service teams.
Call tracking features include reliable dynamic number insertion (DNI) for session-level attribution, local, toll-free, and vanity tracking numbers, and omnichannel attribution across calls, texts, form fills, and chats.
Key contact center features include a browser-based softphone, smart routing options, SMS campaigns, automated call scoring, and smart dialer functionality.
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h5py
The h5py package is a Pythonic interface to the HDF5 binary data format. It lets you store huge amounts of numerical data, and easily manipulate that data from NumPy. For example, you can slice into multi-terabyte datasets stored on disk, as if they were real NumPy arrays. Thousands of datasets can be stored in a single file, categorized and tagged however you want. H5py uses straightforward NumPy and Python metaphors, like dictionary and NumPy array syntax. For example, you can iterate over datasets in a file, or check out the .shape or .dtype attributes of datasets. You don't need to know anything special about HDF5 to get started. In addition to the easy-to-use high level interface, h5py rests on a object-oriented Cython wrapping of the HDF5 C API. Almost anything you can do from C in HDF5, you can do from h5py.
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