LernIX Solutions

In this unit, you learn about the current K-12 cybersecurity landscape and are introduced to how you, as an educator, can prepare to implement cybersecurity measures in your classroom. Cyberattacks on K-12 schools have become a serious concern in recent years, as the education sector increasingly relies on digital technology to support teaching and learning activities. With the widespread adoption of online learning platforms, student information systems, and other digital tools, schools are a rich target for cybercriminals looking to exploit vulnerabilities in these systems. Moreover, schools are often seen as easier targets for cybercriminals when compared to other organizations, as they might have limited resources and technical expertise to secure their networks adequately. Cumulative reported incidents over the past five years show a significant increase in school-focused attacks. Since 2016, the K12 Security Information eXchange cataloged over 1,619 incidents, a rate of ...

After data is ingested, transformed, and loaded, it's ready for others to use. Fabric items provide the flexibility needed for every organization so you can use the tools that work for you. Data scientists can use notebooks or Data wrangler to explore and train machine learning models for AI. Report developers can use the semantic model to create Power BI reports. Analysts can use the SQL analytics endpoint to query, filter, aggregate, and otherwise explore data in lakehouse tables. By combining the data visualization capabilities of Power BI with the centralized storage and tabular schema of a data lakehouse, you can implement an end-to-end analytics solution on a single platform. itil certification training courses malaysia

  Transform and load data Most data requires transformations before loading into tables. You might ingest raw data directly into a lakehouse and then further transform and load into tables. Regardless of your ETL design, you can transform and load data simply using the same tools to ingest data. Transformed data can then be loaded as a file or a Delta table. Notebooks are favored by data engineers familiar with different programming languages including PySpark, SQL, and Scala. Dataflows Gen2 are excellent for developers familiar with Power BI or Excel since they use the PowerQuery interface. Pipelines provide a visual interface to perform and orchestrate ETL processes. Pipelines can be as simple or as complex as you need. java ee enterprise edition training courses malaysia

Another way to access and use data in Fabric is to use  shortcuts . Shortcuts enable you to integrate data into your lakehouse while keeping it stored in external storage. Shortcuts are useful when you need to source data that's in a different storage account or even a different cloud provider. Within your lakehouse you can create shortcuts that point to different storage accounts and other Fabric items like data warehouses, KQL databases, and other lakehouses. Source data permissions and credentials are all managed by OneLake. When accessing data through a shortcut to another OneLake location, the identity of the calling user will be utilized to authorize access to the data in the target path of the shortcut. The user must have permissions in the target location to read the data. Shortcuts can be created in both lakehouses and KQL databases, and appear as a folder in the lake. This allows Spark, SQL, Real-Time intelligence and Analysis Services to all utilize shortcuts when queryi...

Ingesting data into your lakehouse is the first step in your ETL process. Use any of the following methods to bring data into your lakehouse. Upload : Upload local files. Dataflows Gen2 : Import and transform data using Power Query. Notebooks : Use Apache Spark to ingest, transform, and load data. Data Factory pipelines : Use the Copy data activity. This data can then be loaded directly into files or tables. Consider your data loading pattern when ingesting data to determine if you should load all raw data as files before processing or use staging tables. Spark job definitions  can also be used to submit batch/streaming jobs to Spark clusters. By uploading the binary files from the compilation output of different languages (for example, .jar from Java), you can apply different transformation logic to the data hosted on a lakehouse. Besides the binary file, you can further customize the behavior of the job by uploading more libraries and command line arguments. java programming trai...

Now that you understand the core capabilities of a Microsoft Fabric lakehouse, let's explore how to work with one. Create and explore a lakehouse When you create a new lakehouse, you have three different data items automatically created in your workspace. The  lakehouse  contains shortcuts, folders, files, and tables. The  Semantic model (default)  provides an easy data source for Power BI report developers. The  SQL analytics endpoint  allows read-only access to query data with SQL. You can work with the data in the lakehouse in two modes: lakehouse  enables you to add and interact with tables, files, and folders in the lakehouse. SQL analytics endpoint  enables you to use SQL to query the tables in the lakehouse and manage its relational semantic model. oracle java training courses malaysia