Abstract: A user is able to extract financial data, particularly tables, from a document. The table is stored and the user can compare the data in this table with data from similar tables from previous documents. The user can see how financial data has changed historically by looking only at financial tables from the same type of document, for example, only balance sheet tables from annual reports for a specific public company, over many years, and see how the values have changed or whether any new categories or types of data have been added or deleted. From the time series of financial data, the user can gain real intelligence into an entity's financial health.

Abstract: A user is able to extract financial data, particularly tables, from a document. The table is stored and the user can compare the data in this table with data from similar tables from previous documents. The user can see how financial data has changed historically by looking only at financial tables from the same type of document, for example, only balance sheet tables from annual reports for a specific public company, over many years, and see how the values have changed or whether any new categories or types of data have been added or deleted. From the time series of financial data, the user can gain real intelligence into an entity's financial health.

Abstract: A user is able to extract financial data, particularly tables, from a document. The table is stored and the user can compare the data in this table with data from similar tables from previous documents. The user can see how financial data has changed historically by looking only at financial tables from the same type of document, for example, only balance sheet tables from annual reports for a specific public company, over many years, and see how the values have changed or whether any new categories or types of data have been added or deleted. From the time series of financial data, the user can gain real intelligence into an entity’s financial health.

Abstract: A user is able to extract financial data, particularly tables, from a document. The table is stored and the user can compare the data in this table with data from similar tables from previous documents. The user can see how financial data has changed historically by looking only at financial tables from the same type of document, for example, only balance sheet tables from annual reports for a specific public company, over many years, and see how the values have changed or whether any new categories or types of data have been added or deleted. From the time series of financial data, the user can gain real intelligence into an entity's financial health.

Abstract: A user is able to extract financial data, particularly tables, from a document. The table is stored and the user can compare the data in this table with data from similar tables from previous documents. The user can see how financial data has changed historically by looking only at financial tables from the same type of document, for example, only balance sheet tables from annual reports for a specific public company, over many years, and see how the values have changed or whether any new categories or types of data have been added or deleted. From the time series of financial data, the user can gain real intelligence into an entity's financial health.

Abstract: A method of tunneling a data packet through a network communicatively coupled to a datacenter is provided. The datacenter is uniquely addressed within the network. The datacenter has a different internal address space than the network. Transformation rules are recorded for a programmable packet filter in the datacenter. The data packet is received in the programmable packet filter of a host computing device in the datacenter. The received data packet is converted in the programmable packet filter of the host computing device between a stateless tunneling data packet and a datacenter data packet according to the recorded transformation rules. The datacenter data packet is uniquely addressed within the internal address space of the datacenter. The received data packet bypasses any virtual machine processing in the host computing device during the converting. The converted data packet is transmitted from the programmable packet filter in the datacenter.

Abstract: Embodiments relate to enabling clouds to multiplex their public network addresses among private addresses of IPSec gateways while making sure that IPSec tunnel packets are delivered to the private addresses of the IPSec tunnels that they are associated with. When IPSec packets egress from a cloud, the cloud may determine which IPSec tunnel or gateway the IPSec packets are associated with and modify the IPSec packets to identify the associated tunnel or gateway. When IPSec packets ingress to the cloud, the cloud may find identity information in the IPSec packets that identifies the associated tunnel or gateway. The identity information is used to direct the IPSec packets to the associated tunnel or gateway.

Abstract: A method of tunneling a data packet through a network communicatively coupled to a datacenter is provided. The datacenter is uniquely addressed within the network. The datacenter has a different internal address space than the network. Transformation rules are recorded for a programmable packet filter in the datacenter. The data packet is received in the programmable packet filter of a host computing device in the datacenter. The received data packet is converted in the programmable packet filter of the host computing device between a stateless tunneling data packet and a datacenter data packet according to the recorded transformation rules. The datacenter data packet is uniquely addressed within the internal address space of the datacenter. The received data packet bypasses any virtual machine processing in the host computing device during the converting. The converted data packet is transmitted from the programmable packet filter in the datacenter.