• Error message : Cannot convert null to int because it is a non-nullable value type(or) INVALID use of NULL.

• VB.NET offers code execution that runs under the Common Language Runtime (CLR), resulting in robust, stable and secure applications. Both features of the .NET framework are eagerly obtainable in VB.NET.
• VB.NET is object oriented. This is a major addition that VB6 and other earlier releases didn’t have.
• The .NET framework comes with ADO.NET, which follows the disconnected paradigm, i.e. once the required records are fetched the connection no longer exists.
• It also retrieves the records that are expected to be accessed in the immediate future.
• This enhances Scalability of the application to a great extent.
• VB.NET uses XML to transfer data between the various layers in the DNA Architecture i.e. data are passed as simple text strings.
• Error handling has changed in VB.NET. A new Try-Catch-Finally block has been introduced to handle errors and exceptions as a unit, allowing appropriate action to be taken at the place the error occurred thus discouraging the use of ON ERROR GOTO statement. This again credits to the maintainability of the code.

• Pig is a platform for managing large data.
• It uses high level programming to analyse the data.
• The programming is done using the language pig latin.
• It is simple and highly specific.
• The pig Metastore stores all info about the tables. And we can execute spark sql queries because spark can interact with pig Metastore

• Sqoop is a simple tool used for transferring large amount of data.
• It is used for transferring data from hadoop to relational database.
• sqoop can import data from Oracle,MYSQL,SQl.
• Sqoop metastore is a tool for using hosts in a shared metadata repository. Multiple users and remote users execute saved jobs in metastore.

• Staging table is used to stage the exported data.
• Sqoop breaks down method into multiple transactions. A failing job may create partial knowledge.
• This could result in job failing because it could cause duplication of data or even collision while insertion.
• Staging tables are simple database tables that contain business details.
• Staging table acts as an auxiliary table that’s used to transferred data.
• Sqoop breaks down export method into multiple transactions, it’s possible that a failing export job may lead to partial data being committed to the database

• Sqoop is a simple tool that is used for moving data.
• It is generally used move data from non hadoop data stores.
• These non hadoop data stores are the relational databases and data warehouses .
• Sqoop allows the users to specify the target (i.e) the place where the data is to be moved inside of hadoop from relational databases like Oracle,Teredata.
• Data ingestion is important in any big data project because the volume of data is generally in petabytes or exabytes.
• Hadoop Sqoop and Hadoop Flume are the two tools in Hadoop which is used to gather data from different sources and load them into HDFS.

• Sqoop metastore is an internally implemented database that can hold the definition of a given job.
• It includes details like which database,which table,which approach,what query to extract from,what target to write to and so on.
• Consider an array of SQL databases that have the same structure, but are partitioned by for performance reasons.
• Thus we have the same sqoop job running against multiple database instances at the same time, all unified at a single table in Hadoop.
• In order to get parallelization, we generate a job that manages the Sqoop sub-workflows. This results in 500 distinct sqoop jobs.
• Metastore is used to handle these complexities.

• Apache Sqoop is efficiently transferring data between Relational databases and Apache Hadoop.
• It is used to import data from relational databases such as MySQL, Oracle to Hadoop HDFS, and export from Hadoop file system to relational databases.
• It improves the efficiency of data analysis by combining structured data and unstructured data.
• Sqoop stands for SQL for Hadoop.SQL + HADOOP =SQOOP

• Here, some of the key advantages of using splunk which will help you in understanding key features of splunk.

• Identify and resolve issues upto 70% faster.
• Reduces costly escalations by upto 90%.
• Splunk change difficult logs to visual graphs and reports resulting simplified analysis,reporting and troubleshooting

• No separate database requirements like oracle or SQL as splunk stores all data in its index
• Supports any format and any amount of data -enables centralized log management

• Simple to implement and scale
• Continually index all of your IT data in real time.
• Automatically search helpful information inserted in your data, therefore you can’t to spot yourself.
• Search your physical and virtual IT infrastructure for virtually something of interest and find results in seconds.
• Save searches and tag helpful information, to create your system smarter.
• Set up alerts to modify the observation of your system for specific continual events.
• Provide analytical reports with interactive charts, graphs, and tables.
• Share saved searches and reports with fellow Splunk users, and distribute their results to team members and project stakeholders via email.
• Design specialised, information-rich views and dashboards that work the wide-ranging desires of your enterprise.

• The application of splunk are Monitoring, Analyzes machines, security and business performance.
• With intuitive analysis features, machine learning, packaged applications and open APIs, Splunk Enterprise is a comfortable environment that scales from focused use cases to an enterprise-wide analytics backbone.

• A Splunk application is not much more than a structured set of configurations and assets help to achieve an end goal of data collection, indexing, and visualization.
• In order to make a valid Splunk application, you must include the ability to navigate. Without navigation in the application, you would be working on an add-on.
• The performance of application can be monitor vendors Dynatrace and Extrahop have developed apps for Splunk software to help the users to visualize their deep-dive application performance data in the event of all other application data like logs, events, infrastructure performance.

• Proxy logs : It’s better for C2 analysis of files, domains, downloads of DLL/EXE files.
• Anti‐virus logs : It’s good for analysis of malware, vulnerabilities of hosts, laptops, servers, monitor for suspicious file paths.
• Server Operating System logs : These logs are good for analysis of server activities such as users, runaway services, security logs.
• Firewall logs : Logs for network traffic of source/destination ip addresses, ports, protocols.
• Mail logs : Logs for inbound/outbound mail for malicious links, targeted recipients, unauthorized file out bound, data loss, bad attachments.
• Custom apps logs : Logs could be analyze for possible buffer overflow, code injection, SQL injection analyses.

• Intrusion Prevention System logs : To alert on signatures firing off, COTS signatures, threat analysis of bad network packets.
• Database logs : It’s can be capture for authorized access to critical data tables, authorized logons, op ports, admin accounts.
• Virtual Private Network(VPN) logs : Capture logs to analyze users coming into network for situational awareness, monitored foreign ip subnets, compliance monitoring of browsers/apps of connected hosts.
• Authentication logs : To monitor authorized/unauthorized users, times of day of connection, how often, logons/logoffs, BIOS analysis.
• Vulnerability Scan Data : Import data about assets, vulnerabilities, patch data, etc.
• Web Application logs : External facing logs to monitor suspicious SQL keywords, text patterns, REGEX for threats coming in through browser.
• DNS logs: To relate IP address what domain in a client level.
• DHCP logs : To monitor what systems are assign what IP address and how long, how often.

• Active Directory/Domain Controller logs : Monitor user accounts for AD admins, privilege accounts, remote access, multiple admins across the domain, new account creation, event ID’s.
• Badge Access logs : Logs to capture to correlate insider threat, situational awareness, correlate data with authentication logs.
• Router/Switch data (net-‐flow) : Capture this critical data source for APT monitoring, network monitoring, data exfiltration, flow analysis are very important data source.
• Packet Capture logs(PCAP): Very difficult data source to capture for Advanced Persistent Threats, packet analysis, deep packet inspection, malware analysis, etc.
• FW + AV : Will help detect and respond to viruses, worm propagation.
• IPS + AV + FW : Detect/alert on network based attacks such as buffer overflow, reconnaissance scans, code injection.
• PROXY : The web based/application layer is a majority attacks to monitor like: cross-site scripting, session hacking, browse redirects.
• AV + PROXY : Monitor/detect/respond to download of bad files, remote code execution…web-based attacks.
• FW + PROXY : Detect outbound data exfiltration, detect potentially misconfig fw rules.
• IPS + FW : Network packet of signature threats to be monitored.
• AD Server : All user/group modifications, deletes, updates for administrators to be monitored.
• AD + PROXY : Monitor/Detect/Alert on post compromise analysis, lateral movement.

• Splunk is a software environment to give search, analyze and event to machine-generated data collect from the websites, applications, sensors,devices etc.,It create for your IT environment and business.
• Splunk is an advanced,scalable and potent technology that system can be stored indexes and searches log files.It also search the machine-generated data to give operational intelligence.
• The below image will help you how to relate Splunk collects data.

• To report real time health condition.
• The patient’s health record and analyze patterns in the Delve deeper.
• When the patient’s health degrades to be Alarms/Alerts for both the doctor and patient.

• It work can be moved as the ‘Google’ for log files.
• Simpler terms to be searched with the use of Search Processing Language (SPL).
• If the Splunk file system to be store the data directly that means it does not require any back-end or any database
• It doesn’t against any single point of failure to be happened.

Some of the additional components that separately and collectively perform the major operations:

• The System is recognized as a complete system “Fruit Bazaar System. The main actors for this system as Admin, Users, ShippingAgent.

• User can Log-in, add, remove items to cart, register, pay.
• Admin can have privileged login, they can change, modify catalog, to maintain the user data. In cart adding items then they can make an order. Un order database orders are stored.
• The orders are processed and items from the warehouse are delivered to customer by shipping agent.

• CartCustomer/User can browse the catalog and can add items to their cart for ordering. Moreover, Customer can remove items from their cart and after adding items to their cart they can checkout and move to Ordering.
• For Order a customer should to be log-in.
• Registration Maintenance
• Admin can maintain the Catalog. The Catalog contains all items they are in stock with their rates.
• Dynamic rates according to market value can also change the catalog information by Admin. He can add and remove the items from catalog and stocks.

• User can manage their profile. Profile handling includes changing their account information like email, shipping address, passwords.
• If the user has created an invalid account then Admin can be removing the account or can intimate User about any fault in their profile.
• Physical Transaction At the time of delivery A shipping Agent which will take the items from warehouse along with the bill and deliver the item to customer.
• Customer will pay the respective bill and the bill id will be stored in transaction database.
• Cash transaction should be keeping record like in transaction database which will store bill amount and bill id.
• LOGINUser enter their login-id along with password. If the entered data is valid combination then homepage will be displayed.
• Otherwise a message intimating user about them invalidate login details.
• After placing Order Customer will be intimated by an order confirmation mail and sending a SMS containing order details and delivery time.

• It means that the ticket you’re currently in is automatically refreshed when it’s modified, with any changes highlighted in green.
• Sometimes, a different agent may submit a reply or change a ticket property (such as an assignee, tag or ticket type). Other times, ticket properties may be changed by a trigger, automation or a macro.
• It could even be a new reply from your customer. In either case, your agents will be able to see these changes reflected in their help desk instantaneously.
  • Ticket view
  • Ticket filters
  • Ticket list

• For example you’re viewing a ticket, here’s what will happen if another agent submits their own changes. All ticket property changes (including those changed by a trigger, automation or macro) will be highlighted in green & your previously made changes reset.
  • ticket status
  • assignee
  • email
  • CC
  • subject
  • tags
  • priority
  • type

• New replies will have a green background with “NEW” appearing in the ticket header. If you’ve been working on a reply, it will remain intact.
• New internal notes will have an orange background with “NEW” appearing in the ticket header. If you’ve been working on a reply, it will remain intact.
• If a ticket is deleted while you’re viewing it, the ticket will disappear and you’ll see “Ticket #123 has been deleted by (agent’s name)”.

• Ticket filters (also known as ticket views) organize tickets according to your workflows and also displayed in real-time.
• When a new, shared (i.e. visible to all agents) filter is created, a private filter is made shared or vice versa.
• When the filter’s name is changed. If the search query or sorting properties are changed, they will not be reflected in real-time.
• When a ticket appears or disappears from a filter, the number nearby the filter will be changed consequently.
• When a new ticket appears or disappears from a filter you’re currently in.

• The ticket list is the middle column which shows a list of tickets matching your current search query or filter. When new tickets are added, moved or deleted they will appear or disappear from the ticket list immediately.
• Finally, check out Agent collision detection in tickets. It helps you see who is viewing, updating or replying to a ticket.

• The Internet dealings Server (ITS) shopper is that the system shopper wherever the launch transactions area unit dead once agents use the IC WebClient.You would like to log in to the remote system (for example, SAP ERP) to assemble the data required to take care of the computer address, however the settings area unit created within the CRM system.
• The Interaction Center (IC) WebClient could be a thin-client, highly-optimized desktop application for interaction center agents. It provides a framework for process IC WebClient functions.