Zoho Releases Security Update for ADSelfService Plus

This article is contributed. See the original author and article here.

Zoho has released a security update on a vulnerability (CVE-2021-40539) affecting ManageEngine ADSelfService Plus builds 6113 and below. CVE-2021-40539 has been detected in exploits in the wild. A remote attacker could exploit this vulnerability to take control of an affected system. ManageEngine ADSelfService Plus is a self-service password management and single sign-on solution for Active Directory and cloud apps. Additionally, CISA strongly urges organizations ensure ADSelfService Plus is not directly accessible from the internet.

CISA encourages users and administrators to review the Zoho advisory for more information and to update to ADSelfService Plus build 6114.

Microsoft acquires Clipchamp to empower creators

Microsoft acquires Clipchamp to empower creators

This article is contributed. See the original author and article here.

Microsoft acquires Clipchamp to help you express yourself through the power of video. The Clipchamp team is a creative powerhouse dedicated to quality and great customer outcomes—and we welcome them wholeheartedly as kindred spirits.

The post Microsoft acquires Clipchamp to empower creators appeared first on Microsoft 365 Blog.

Brought to you by Dr. Ware, Microsoft Office 365 Silver Partner, Charleston SC.

How finance leaders can leverage intelligent automation to unleash innovation

How finance leaders can leverage intelligent automation to unleash innovation

This article is contributed. See the original author and article here.

For organizations to thrive in the modern environment, they need to innovate, and innovation takes time. Leaders that expect teams to be innovative without creating time for the innovation process will likely be disappointed by the results. But how can teams deliver more with less? One possible opportunity for finance leaders is to leverage intelligent automation and other emerging technologies.

It’s widely accepted that intelligent automation can improve efficiency, reduce costs, and improve productivity. It can also increase team member engagement and satisfaction. However, what’s often overlooked is the broader impact on innovation. With less time spent on manual tasks, employees can reinvest their energy into work that requires more creativity and critical thinking. Adopting intelligent automation and emerging technology now allows forward-thinking finance leaders to remain competitive amidst today’s complex challenges.

Meet rising expectations

As business complexity rises, organizations increasingly turn to their senior finance leaders for strategic direction and to drive business transformation. Chief financial officers (CFOs) play significant roles in companies’ transformation efforts, and the transformations demand expanded support from finance.

As these expectations continue to rise for finance leaders, they must look for opportunities to leverage technology, such as AI-driven insights, to enhance financial decision-making within their organizations. Moreover, by projecting future outcomes, organizations can make more informed decisions today. Microsoft Dynamics 365 Finance is helping leading organizations in these efforts and paving the way for innovation in the process.

Take advantage of emerging technologies

To meet the demands of modern business, many finance teams are turning to emerging technologies, such as intelligent automation, AI, and machine learning, to help streamline processes, improve accuracy, and maximize compliance. Much of finance operations can be fully or partially automated using currently available technologies. It follows that leaders’ who embrace emerging technologies to automate finance operations can free up significant resources in their organizations to focus on strategic leadership and innovation.

Indeed, financial institutions surveyed by Statista who are already using AI reported reduced operational costs, increased data-driven decision making, and even improved customer satisfaction. Internally, these institutions also saw benefits like reducing team member workload.1

Despite the benefits, the adoption of AI technologies remains low. A potential reason for the low adoption rate is that AI is seen as more complicated and has a less proven use case, unlike other emerging technologies such as the cloud. In financial firms, significantly fewer used AI-driven technologies than cloud-based platforms.

Considering AI’s reported and potential benefits alongside its lower adoption rate, the case can be made that finance leaders who leverage this technology now can do more than free up time for team members to focus on innovation. They can also create a strategic advantage for their organization in the short term.

With so much to gain, let’s look at a few specific examples of where organizations can leverage AI to increase efficiency and improve competitive advantage.

Accounts receivable

Organizations often find it difficult to predict when a customer will pay their invoices. This situation can lead to less accurate cash flow forecasts, collections processes that are started too late, and orders released to customers who may default on their payment.

Compounding the problem is the fact that cash collection is generally a reactive process. All too often, managers are stuck with rising receivables and manual data entry. It’s why many people are still pulling data from their enterprise resource planning (ERP) into Excel spreadsheets a process that quickly eats through valuable time. Therefore, the ability to shift towards a proactive, intelligent approach to cash collection is invaluable.

For example, in Dynamics 365 Finance, it’s now possible to develop a prediction model to manage accounts receivable with AI-driven technologies. In this scenario, an AI model predicts which customers are likely to pay on time, which are not, and even provides a margin of error to consider. Organizations can use predictions in this way to create collection strategies to enable intelligent automations. This enables finance leaders to proactively encourage customers to pay ahead of time or develop new strategies and systems to make payments more manageable. Leveraging an automated, AI-based prediction model also means more time for employees to focus on higher-level problem solving, planning, or customer service.

Ultimately, a proactive, automated collections process enables teams to improve margins and efficiency while reducing risk and late payments.

Cash flow forecasting

Traditional cash flow forecasting can be tedious and problematic. For example, data often gets stuck in siloes, leaving people with complex Excel spreadsheets that are disconnected, time-consuming, and error-prone. It can also be hard to develop and deploy models when cash flow forecasting is based on institutional knowledge. And when it comes to measuring performance and accuracy, excel spreadsheets often fall short.

At Microsoft, we have built an intelligent cash flow solution that uses AI and machine learning. This new solution allows users to first integrate data from external systems to Dynamics 365 Finance using the data import and export framework. Then, users can create a forecast of cash flow and cash positions based on customer payment predictions as well as bank balance and time series forecasting. The system also allows users to save cash flow forecasts and then measure forecast performance when the financials have been realized.

Learn more in our recent webinar: Optimize financial operations with AI-infused processes.

Dynamics 365 Finance

Dynamics 365 Finance is a financial management suite that enables enterprise organizations to monitor the performance of their global financial operations in real-time, predict future outcomes, and make data-driven decisions to drive growth. If your organization is looking for ways to leverage automation and AI, Dynamics 365 Finance can help to unify your data and automate your business processes.

You can learn more about how Dynamics 365 Finance can enable your organization to improve efficiency and quality with AI-infused finance processes in our recent “Improve efficiency and quality with AI-infused finance processes” blog or get started today with a Dynamics 365 demo or free trial.


1- “Benefits from adoption of AI in financial services sector worldwide 2020, by region”, F. Norrestad, Statista, Jun. 28, 2021.

The post How finance leaders can leverage intelligent automation to unleash innovation appeared first on Microsoft Dynamics 365 Blog.

Brought to you by Dr. Ware, Microsoft Office 365 Silver Partner, Charleston SC.

How finance leaders can leverage intelligent automation to unleash innovation

Download the training module for Field Service (Dynamics 365) mobile app

This article is contributed. See the original author and article here.

The Field Service (Dynamics 365) mobile app helps frontline workers stay connected to essential information while out in the field. Frontline workers use the mobile app to view schedules, record notes, and examine customer, work order, and asset information.

Download the training module, Field Service (Dynamics 365) mobile app in a day, to learn how to set up, use, and configure the Field Service (Dynamics 365) mobile app. This self-paced, on-demand training is a step-by-step guide through exercises based on business scenarios from real customers.

What you’ll learn

After completing the online training module, which can be completed in about four hours, you will be able to:

  • Download and sign in to the mobile app and interact with Dynamics 365 Field Service information like bookings and work orders.
  • Perform common configurations like editing the tables, forms, views, and columns displayed in the mobile app. Set up “offline first” synchronization so the mobile app works without internet access.
  • Perform more advanced configurations and customizations like location tracking, push notifications, barcode scanning, and mobile workflows to accommodate more business requirements and processes.
  • Learn best practices to implement the Field Service (Dynamics 365) mobile app, including migrating from the previous mobile app.

What you’ll need

To complete the “Field Service (Dynamics 365) mobile app in a day” training, you will need:

  • Internet connection
  • PC computer or laptop
  • Android or iOS mobile phone or tablet

No prior experience is needed. The module starts with setting up a new Dynamics 365 Field Service environment from scratch and builds from there. If you are already using Dynamics 365 Field Service, you can use your existing environment.

More about the Field Service (Dynamics 365) mobile app

The Field Service (Dynamics 365) mobile app is a model-driven app built on Microsoft Power Platformthat is optimized for mobile interfaces. This means the process to manage, configure, customize, and upgrade the mobile app is the same process as it is for other web-based Dynamics 365 apps. It also means the mobile app uses Microsoft Power Platform functions and leverages new platform capabilities.

Next steps

To begin your self-paced tutorial, download the training module Field Service (Dynamics 365) mobile app in a day.

The post Download the training module for Field Service (Dynamics 365) mobile app appeared first on Microsoft Dynamics 365 Blog.

Brought to you by Dr. Ware, Microsoft Office 365 Silver Partner, Charleston SC.

Check the health of your exported Azure Sentinel logs in your ADX cluster

Check the health of your exported Azure Sentinel logs in your ADX cluster

This article is contributed. See the original author and article here.

More and more Azure Sentinel customers are opting for long-term retention of their logs in Azure Data Explorer (ADX), either due to compliance regulations, or because they still want to be able to perform investigations on their archived logs in the event of a security incident.


As the Azure Sentinel ingestion price includes 90 days of retention for free, the option of keeping the logs for longer periods in Azure Data Explorer is preferred by many (see Using Azure Data Explorer for long term retention of Azure Sentinel logs – Microsoft Tech Community). 


 


Even though the Azure Sentinel + ADX solution requires little to no maintenance, we wanted to provide a solution for our customers to keep an eye on the number of events and overall status of their ADX clusters and databases. For this reason, we have created two tools: the ADXvsLA workbook and the ADX Health Playbook. The workbook will allow you to have a look at the number of logs on Azure Sentinel & ADX and the overall health of your ADX cluster. The playbook will send you a warning if an unexpected delay in the ingestion of ADX is detected.


 


 


Below, we will describe both in more detail:


 


ADXvsLA Workbook


 


When you open the workbook, you can select the following parameters:



  • the ADX cluster and database

  • the Azure Sentinel workspace from which the logs are exported to the aforementioned ADX cluster,

  • as well as the time range for which you want to see data


Use the Show Help toggle to see a detailed explanation of each section.


 


1.png


 


Raw Tables


When you ingest logs from Azure Sentinel to ADX, the logs are first ingested into an intermediate table with raw data. This raw data is updated by a function with an update policy and is saved to its destination table with the correct mapping. Afterwards, the data is deleted, which is why you will typically see that these raw tables are empty. The retention policy should also be set for 0 days.


 


2.png


 


Final ADX Tables


In this section, you will see information about the final ADX tables, which have the right schema and can be queried from Azure Sentinel. You will find information regarding the row count, size, retention policy and hot cache size etc.


4.png


 


Select one of the table names to generate the comparison section. This is where you can see the differences between the table on ADX and on your Log Analytics workspace. Then, select the time range for which you want to see the comparison.


In the table you will find:



  • The number of entries in ADX, in Log Analytics, and the difference in number of logs between them.

  • How long it has been since the last log was received

  • The timestamp of the last logs.

  • The number of new logs received in Log Analytics since the last log in ADX was received


3.png


 


Notice the New in Log Analytics column





    • In the screenshot, you can see there are 52 logs in the “New in Log Analytics” column. This means that, at the time we compared the tables, there were 52 entries that had not reached ADX yet.
      If this happens, you should compare the timestamp and the difference for the last log that was received. In this case, it is around 15 minutes. Delays of 30 minutes or less are expected, so this means your tables are working as expected.

    • It is also possible that you see a negative number in the New in Log Analytics column. This could happen if, due to the lag in ADX, there were Log Analytics logs from the previous period that were received in ADX during the current period. Let’s suppose that you ingested 1000 logs in Log Analytics on the previous 24h window, but only 990 reached ADX in that period; and then you ingested 1000 logs again on the current 24h window, and all those logs, plus the 10 logs from the previous day, reached ADX. In this case, you will see that the “New in Log Analytics” column would say -10. In these cases, you only need to look at the LastTM difference. If it is around 30 minutes or less, then it will be fine.


     




Finally, at the bottom of the workbook you will see metrics regarding events received, events dropped, received data, volume and other metrics.


 


ADX Health Playbook


 


The ADX Health Playbook compares the number of logs in your Azure Sentinel tables and ADX tables periodically (every 24h by default) and sends you a warning via email if it detects a difference in the number of logs that may require your attention (that is, in the “New in Log Analytics” column mentioned previously). As it takes logs a few minutes to reach ADX after having been ingested into Log Analytics, the query in the playbook by default looks back at the period between the last 25h and last 30min.


Please read the accompanying readme.md file on GitHub to set it up.


 


We hope you find these tools useful! If you have any suggestions for improving this content or any questions, please leave us a comment.