Leveraging Big Data Sample Clauses

Leveraging Big Data. The American Public Transportation Association (APTA) conducted a study on big data and the public transit industry. This was an APTA initiative that involved discussions with the public transit agencies and the private sector. As part of this effort, a survey was conducted that revealed that 94 percent of agencies are using big data techniques and methods to improve efficiencies. APTA’s Leveraging Big Data in the Public Transportation Industry (Xxxxxxx and Xxxxxx- Xxxxxxxx, 2019) provides valuable insights on how to use of big data to enhance public transportation services. The term big data usually refers to large and continuous datasets that need to be structured before analyzing and used to inform decisions and solve problems. Many organizations in different industries have used large quantities of data to reduce costs, increase efficiencies, and improve decision making. Transit agencies are using the large amount of data collected by the different systems to improve their service and efficiency. These systems include automatic vehicle location, automatic passenger counting, and automatic fare collection systems. There are other sources of data that are not automatically created, but they are entered by agency employees. Breaking down the collected data is another important step to complete the necessary analysis of the information. In addition, new technologies like high performance computing (HPC) or Amazon Web Services (AWS) can help with processing big data. Having a cloud storage permits the sharing of data across an entire organization, allowing convenient access for different departments (Xxxxxxx and Xxxxxx- Xxxxxxxx, 2019). Big data can have many functions. Transit agencies are using it to improve and optimize operations and maintenance by allowing a comprehensive analysis of the equipment stating their current conditions. Once the analysis is completed, the AWS system can be used to create a predictive model of the equipment condition and performance to help the agency to foresee bus breakdowns. Predictive modeling is being used in other capacities to improve efficiencies and reduce costs. For example, predictive modeling can be used to monitor, manage, and react to potential operator absenteeism, allowing the agencies to provide backup in order to avoid service interruptions (Xxxxxxx and Xxxxxx-Xxxxxxxx, 2019). Transportation agencies are starting to use big data for safety and security purposes. Big data tools can be used to analyze the netw...
AutoNDA by SimpleDocs

Related to Leveraging Big Data

  • Safeguarding Information Not to use or disclose any information concerning a recipient of services under this contract for any purpose not in conformity with state and federal law except upon written consent of the recipient, or the responsible parent or guardian when authorized by law.

  • Links to Third Party Websites In your use of the Service and/or the Company’s website, you may encounter various types of links that enable you to visit websites operated or owned by third parties (“Third Party Site”). These links are provided to you as a convenience and are not under the control or ownership of the Company. The inclusion of any link to a Third Party Site is not (i) an endorsement by the Company of the Third Party Site, (ii) an acknowledgement of any affiliation with its operators or owners, or (iii) a warranty of any type regarding any information or offer on the Third Party Site. Your use of any Third Party Site is governed by the various legal agreements and policies posted at that website.

  • Originating Switched Access Detail Usage Data A category 1101XX record as defined in the EMI Telcordia Practice BR-010-200- 010.

  • Sharing Information with Billers You authorize us to share identifying personal information about you (such as name, address, telephone number, Xxxxxx account number) with companies that you have identified as your Billers and which we have identified as offering electronic bills for purposes of matching your identity on the Service’s records and the Xxxxxx’x records to (a) activate your affirmative request for electronic bills, and/or (b) confirm your eligibility for “trial basis” electronic bills.

  • Line Information Database 9.1 LIDB is a transaction-oriented database accessible through Common Channel Signaling (CCS) networks. For access to LIDB, e-Tel must purchase appropriate signaling links pursuant to Section 10 of this Attachment. LIDB contains records associated with End User Line Numbers and Special Billing Numbers. LIDB accepts queries from other Network Elements and provides appropriate responses. The query originator need not be the owner of LIDB data. LIDB queries include functions such as screening billed numbers that provides the ability to accept Collect or Third Number Billing calls and validation of Telephone Line Number based non-proprietary calling cards. The interface for the LIDB functionality is the interface between BellSouth’s CCS network and other CCS networks. LIDB also interfaces to administrative systems.

  • Updating Your Information You must provide updated information to any person to whom you claimed to be an exempt payee if you are no longer an exempt payee and anticipate receiving reportable payments in the future from this person. For example, you may need to provide updated information if you are a C corporation that elects to be an S corporation, or if you no longer are tax exempt. In addition, you must furnish a new Form W-9 if the name or TIN changes for the account, for example, if the grantor of a grantor trust dies. Penalties Failure to furnish TIN. If you fail to furnish your correct TIN to a requester, you are subject to a penalty of $50 for each such failure unless your failure is due to reasonable cause and not to willful neglect. Civil penalty for false information with respect to withholding. If you make a false statement with no reasonable basis that results in no backup withholding, you are subject to a $500 penalty. Criminal penalty for falsifying information. Willfully falsifying certifications or affirmations may subject you to criminal penalties including fines and/or imprisonment.

  • Billing Information 6.1 NLT and the RL shall provide each other with information within their possession that is necessary to allow them to provide accurate and timely billing to each other and to any other relevant third parties.

  • Data To permit evaluation of requests under paragraph (c) of this clause based on unreasonable cost, the Contractor shall include the following information and any applicable supporting data based on the survey of suppliers: Foreign and Domestic Construction Materials Cost Comparison Construction material description Unit of measure Quantity Cost (dollars) * Item 1: Foreign construction material Domestic construction material Item 2 Foreign construction material Domestic construction material [List name, address, telephone number, and contact for suppliers surveyed. Attach copy of response; if oral, attach summary.] [Include other applicable supporting information.] (*Include all delivery costs to the construction site.]

  • Authoritative Root Database To the extent that ICANN is authorized to set policy with regard to an authoritative root server system (the “Authoritative Root Server System”), ICANN shall use commercially reasonable efforts to (a) ensure that the authoritative root will point to the top-­‐level domain nameservers designated by Registry Operator for the TLD, (b) maintain a stable, secure, and authoritative publicly available database of relevant information about the TLD, in accordance with ICANN publicly available policies and procedures, and (c) coordinate the Authoritative Root Server System so that it is operated and maintained in a stable and secure manner; provided, that ICANN shall not be in breach of this Agreement and ICANN shall have no liability in the event that any third party (including any governmental entity or internet service provider) blocks or restricts access to the TLD in any jurisdiction.

  • Sensitive data Where the transfer involves personal data revealing racial or ethnic origin, political opinions, religious or philosophical beliefs, or trade union membership, genetic data, or biometric data for the purpose of uniquely identifying a natural person, data concerning health or a person’s sex life or sexual orientation, or data relating to criminal convictions and offences (hereinafter ‘sensitive data’), the data importer shall apply the specific restrictions and/or additional safeguards described in Annex I.B.

Time is Money Join Law Insider Premium to draft better contracts faster.