Preliminary findings3/1/2023 ![]() They highlight the likely sources of information and advice employers will seek as they complete activities to comply with the reforms. This shows encouraging signs that automatic enrolment is achieving its objective of increasing the number of people saving into a workplace pension. The findings also show a significant increase in the proportion of private sector employees saving into a workplace pension. ![]() levels of employee opt-out as reported in Automatic enrolment opt-out rates: findings from research with large employers.levels of awareness of the workplace pension reforms among small and medium employers as published by The Pension Regulator Employers’ awareness, understanding and activity relating to workplace pension reforms (2014). ![]() Telephone interviews with 3,079 organisations took place between 19 June and 4 November 2013.įindings on employer awareness of the workplace pension reforms and the proportion of employees opting out of a workplace pension following automatic enrolment are consistent with other published research. The 2013 EPP was conducted among a representative sample of private sector employers in Great Britain, drawn from the Office for National Statistics Inter-Departmental Business Register (IDBR). A major focus of the survey is on the early impacts of these reforms, as well as the intentions and levels of awareness among employers who are not yet directly affected by the reforms. This is the first survey undertaken since the implementation of the workplace pension reforms. ![]() The 2013 employers’ pension provision ( EPP) survey is the tenth in the series and has collected information on the current nature and extent of pension provision among private sector organisations. A research report by John Forth and Lucy Stokes (National Institute of Economic and Social Research) and Catherine Grant and Sam Sullivan (TNS BMRB). ![]()
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MongoDB 3.2 introduces MongoDB Compass - a graphical tool that allows you to easily analyse and understand your database schema, as well as allowing you to visually construct queries, all without having to know MongoDBs query syntax: MongoDB Compass was built to address 3 main goals: Schema discovery. How many restaurants offer hamburgers and opened in 2010 or later? 8. MongoDB Compass is a GUI based tools (unline MongoDB Shell) to interact with local or remote MongoDB server and databases. It is defined as a sequence of stages or data aggregate operations. In MongoDB, there are three ways to perform aggregate are as follows. What are the borough and the coordinates of the restaurant with the most employees in the database? Return the borough name and the coordinates of the restaurant. Below is the working of aggregate command: MongoDB aggregate is used to process various data types and return a calculated result using processed data. What are the three most popular culsines of the restaurants that are located in Brooklyn borough and have greater than 20 employees? Please present the cuisines and the total number of restaurants by cuisine. Present the results based on lowest to highest average number of employees (Round query result to second decimal) Return the average number of employees by borough among restaurants that offer only the takeout option and opened in 2010. What are the streets and culsines of the two oldest restaurants in Brooklyn? Return the street names and cuisines of the restaurants. Limit the Number of Returned DocumentsExport Query to Specific Language. explain () method from Embedded MongoDB Shell in Compass. The Explain Plan tab is not available for aggregation commands. located in Bronx, compute the number of restaurants that opened In each year 3. The Explain Plan tab is not available if you are connected to Data Lake. Of the restaurants that offer 4 options and Is. 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