This document discusses data exchange in Linnworks, including importing, exporting, and querying data from third party sources. It covers setting up scheduled or instant uploads and extractions of data in a consistent CSV format. The presentation provides rules for the CSV file format, such as avoiding scientific notation, properly formatting special characters, using unique column headers, and including default values, expressions, and extended properties. It also discusses automating data exchange on schedules and running ad hoc query reports to access data as needed.
We had a change in government with a ‘change agenda’. Downturn in the global oil market dampening Nigeria’s economic outlook. Advertising industry had it rough in spite of the election windfall. Weakened economies of many states dislocated disposable income of consumers across the country. A new political leadership brings optimism with the biggest budget in Nigeria’s history. In 2016, agencies will have to do more with less, get more creative and widen their scope of competence. Boom in modern retail would increase brand activation and BTL campaigns. Technology would continue to change the way brands and consumers relate but the latter would take more control of their media consumption. We can’t predict the future. This outlook is an expression of our expertise and consistent thought leadership.
We had a change in government with a ‘change agenda’. Downturn in the global oil market dampening Nigeria’s economic outlook. Advertising industry had it rough in spite of the election windfall. Weakened economies of many states dislocated disposable income of consumers across the country. A new political leadership brings optimism with the biggest budget in Nigeria’s history. In 2016, agencies will have to do more with less, get more creative and widen their scope of competence. Boom in modern retail would increase brand activation and BTL campaigns. Technology would continue to change the way brands and consumers relate but the latter would take more control of their media consumption. We can’t predict the future. This outlook is an expression of our expertise and consistent thought leadership.
Overview of Apache SystemML by Berthold Reinwald and Nakul JindalArvind Surve
This deck will provide SystemML architecture, how to get documentation for usage, algorithms etc. It will explain usage of it through command line or through notebook.
This presentation provides a technical overview of IBM Optim and its benefits.
Three areas of focus:
Mitigate Risk: Much of the “data related” risk that an organization carries is related to keeping sensitive data private, preventing data breaches, and safely storing and retiring data that is no longer required on the online systems. Companies must comply to regulations and policies, and lack of proper data protection can lead to penalties, including damaging a company’s reputation.
Deal with Data Growth: Another challenge is dealing with the explosive data growth for many applications. Without properly managing the data volume, companies will see the impact in the performance of their system over time. This is particularly a problem when service level agreements (SLA’s) are in place that mandate set response times.
Control Costs: The costs of managing data spans across initial design of the data structure throughout all lifecycle phases - until ultimately retiring the data. IT staff is under constant pressure to deliver more for less. Some major costs for managing data include storage hardware costs, storage management costs (archiving, storing, retrieving, etc.), and costs of protecting the data per compliance regulations.
Automated Product Data Preparation: Processes, Methods and AlgorithmsOnedot
Product data is one of the most complex kind of data. Find out how state-of-the-art automated product data preparation is done using a smart mix of probabilistic and statistical methods, paired with latest algorithms of machine learning and artificial intelligence.
Onedot's artificial intelligence (AI)-driven software helps businesses reduce manual work in product data management by 20x, speed up time-to-market by 90% and increase revenue up to 10%. Onedot makes this possible by radically improving data quality–automating the data integration, cleaning and categorisation process.
Onedot features a user-friendly web interface designed for non-technical users. Unlike traditional rule-based ETL or scripting tools, Onedot is a ‘plug-and-play' system that continuously learns from business expert feedback and adapts to constantly changing data formats, structures, and nomenclatures.
To learn more about Onedot, visit: https://www.onedot.com.
The file contains samples which include Data Enrichment, UNSPSC classification, Eclass (eCl@ss) classification, Taxonomy Development, and Schema Development for the industry verticals of MRO, Electrical, Electronics, Automotive, and pharmaceutical.
Comcast is the largest cable and internet provider in the US, reaching more than 30 million customers, and continues to grow its presence in the EU with the acquisition of Sky. Over the last couple years, Comcast has shifted focus to the customer experience.
Overview of Apache SystemML by Berthold Reinwald and Nakul JindalArvind Surve
This deck will provide SystemML architecture, how to get documentation for usage, algorithms etc. It will explain usage of it through command line or through notebook.
This presentation provides a technical overview of IBM Optim and its benefits.
Three areas of focus:
Mitigate Risk: Much of the “data related” risk that an organization carries is related to keeping sensitive data private, preventing data breaches, and safely storing and retiring data that is no longer required on the online systems. Companies must comply to regulations and policies, and lack of proper data protection can lead to penalties, including damaging a company’s reputation.
Deal with Data Growth: Another challenge is dealing with the explosive data growth for many applications. Without properly managing the data volume, companies will see the impact in the performance of their system over time. This is particularly a problem when service level agreements (SLA’s) are in place that mandate set response times.
Control Costs: The costs of managing data spans across initial design of the data structure throughout all lifecycle phases - until ultimately retiring the data. IT staff is under constant pressure to deliver more for less. Some major costs for managing data include storage hardware costs, storage management costs (archiving, storing, retrieving, etc.), and costs of protecting the data per compliance regulations.
Automated Product Data Preparation: Processes, Methods and AlgorithmsOnedot
Product data is one of the most complex kind of data. Find out how state-of-the-art automated product data preparation is done using a smart mix of probabilistic and statistical methods, paired with latest algorithms of machine learning and artificial intelligence.
Onedot's artificial intelligence (AI)-driven software helps businesses reduce manual work in product data management by 20x, speed up time-to-market by 90% and increase revenue up to 10%. Onedot makes this possible by radically improving data quality–automating the data integration, cleaning and categorisation process.
Onedot features a user-friendly web interface designed for non-technical users. Unlike traditional rule-based ETL or scripting tools, Onedot is a ‘plug-and-play' system that continuously learns from business expert feedback and adapts to constantly changing data formats, structures, and nomenclatures.
To learn more about Onedot, visit: https://www.onedot.com.
The file contains samples which include Data Enrichment, UNSPSC classification, Eclass (eCl@ss) classification, Taxonomy Development, and Schema Development for the industry verticals of MRO, Electrical, Electronics, Automotive, and pharmaceutical.
Comcast is the largest cable and internet provider in the US, reaching more than 30 million customers, and continues to grow its presence in the EU with the acquisition of Sky. Over the last couple years, Comcast has shifted focus to the customer experience.
IFS Manufacturing customer´s experience of using IFS ApplicationsIFS
Find out how CDF Corporation uses IFS Applications and, in particular, mobility on the shop floor and how IFS Touch Apps are being deployed in the business.
Over the last year the lightweight DITA document types have been used to prototype content from a variety of different sources within IBM, including marketing, learning and training, technical articles, and internal policies/procedures. This presentation will introduce the lightweight DITA document types, demonstrate the feasibility of using a lightweight but still structured approach for integrating content across the enterprise content ecosystem, and show how lightweight DITA can be implemented using either XML or HTML5 as the base.
Its a project report for eAgriculture..
Its consist of samples of this project..
Front end :JSP
Backend:MySQL
For ore details want u know,then contact me .
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2. Having worked at Linn Systems since January 2012 within the Support, Development and Implementation teams the
knowledge I have gained allows me to provide advice to team members, partners and clients alike on best practices for
setting up the system, ensuring each client has the opportunity to reap the benefits that can be achieved through using
Linnworks for inventory, order and listing management
Mark Aldous
4. Data Exchange
Import
Automating the updating of Linnworks
data through either scheduled or instant
uploads from 3rd party sources
Export
Automating the process for extracting
data from Linnworks and providing it in a
consistent format for use by 3rd parties
Query Data
Access to both configurable pre-defined
reports and bespoke custom reports
generated on an ad-hoc basis
5. File Format
CSV
Industry standard for data exchange
Simple
Compact
Support
RULES
Remember these simple rules to enhance your experience
Scientific format
Special characters
Quotation marks
Column headers
Default Values
Expressions
Extended Properties
- Avoid importing 3.00638E+12
- Importing Ñ,ó,à,ô,è
- Keep your data where you want it
- Ensure unique headers
- Make your files smaller
- Work with the data your way
- Shared data for listing
6. File Format Rules
SKU Title Barcode
050-OTH-ADANA Othmani Adana Berry 50g 4.00638E+12
050-OTH-AEGEAN Othmani Aegean Spice 50g 4.00638E+12
050-OTH-AKKAR Othmani Akkar Berry 50g 4.00638E+12
050-OTH-ALARB Othmani Al Arab Grape Mint 50g 4.00638E+12
050-OTH-BYBLOS Othmani Byblos Peach 50g 4.00638E+12
050-OTH-DAMASCUS Othmani Damascus Strawberry 50g 4.00638E+12
050-OTH-IZMIR Othmani Izmir Melon 50g 4.00638E+12
050-OTH-KOURA Othmani Koura Fruit Mix 50g 4.00638E+12
050-OTH-MARRAKECH Othmani Marrakech Mint 50g 4.00638E+12
050-OTH-NABATIEH Othmani Nabatieh Strawberry 50g 4.00638E+12
050-OTH-SAMSUN Othmani Samsun Baklava 50g 4.00638E+12
050-OTH-STAR Othmani Star of Al Hamra 50g 4.00638E+12
7. File Format Rules
SKU Title Colour Colour_FR
100001 T-Shirt Blue, Size S Deep Blue bleu foncé
100002 T-Shirt Blue, Size M Deep Blue bleu foncé
100003 T-Shirt Blue, Size L Deep Blue bleu foncé
100004 T-Shirt Blue, Size XL Deep Blue bleu foncé
100005 T-Shirt Blue, Size XXL Deep Blue bleu foncé
100006 T-Shirt Red, Size S Light Red rouge léger
100007 T-Shirt Red, Size M Light Red rouge léger
100008 T-Shirt Red, Size L Light Red rouge léger
100009 T-Shirt Red, Size XL Light Red rouge léger
100010 T-Shirt Red, Size XXL Light Red rouge léger
100011 T-Shirt Green, Size S Emerald Green vert émeraude
11. File Format Rules
SKU Level
050-OTH-ADANA In Stock
050-OTH-AEGEAN In Stock
050-OTH-AKKAR Low Stock
050-OTH-ALARB Out of Stock
050-OTH-BYBLOS In Stock
050-OTH-DAMASCUS Low Stock
050-OTH-IZMIR In Stock
050-OTH-KOURA Out of Stock
050-OTH-MARRAKECH Low Stock
050-OTH-NABATIEH In Stock
050-OTH-SAMSUN Low Stock
050-OTH-STAR Out of Stock
12. File Format Rules
SKU Title Weight Category Material Size Colour
100001 T-Shirt Blue, Size S 50 Mens Clothing 100% Cotton S Blue
100002 T-Shirt Blue, Size M 50 Mens Clothing 100% Cotton Medium Blue
100003 T-Shirt Blue, Size L 50 Mens Clothing 100% Cotton L Blue
100004 T-Shirt Blue, Size XL 50 Mens Clothing 100% Cotton XL Blue
100005 T-Shirt Blue, Size XXL 50 Mens Clothing 100% Cotton XXL Blue
100006 T-Shirt Red, Size S 50 Mens Clothing 100% Cotton S Red
100007 T-Shirt Red, Size M 50 Mens Clothing 100% Cotton M Red
100008 T-Shirt Red, Size L 50 Mens Clothing 100% Cotton L Red
100009 T-Shirt Red, Size XL 50 Mens Clothing 100% Cotton XL Red
100010 T-Shirt Red, Size XXL 50 Mens Clothing 100% Cotton XXL Red