- Excel Meaning
- Text Data Definition In Excel
- Data Marker In Excel Definition
- Data Source In Excel Definition
After connecting to external data, you can also automatically refresh (or update) your Excel workbooks from the original data source whenever the data source is updated with new information. Connection information is stored in the workbook and can also be stored in a connection file, such as an Office Data Connection (ODC) file (.odc) or a Data. Find the Consolidate feature in the Data tab in the Data Tools group. Excel will display a list of functions. Select a function, such as sum, with which to consolidate the source data.; Select the data range in each source spreadsheet. Click the Add button next to the All References listbox to add that set of data to the consolidation.; Click the Create Links to Source Data checkbox if you're.
Data mapping is crucial to the success of many data processes. One misstep in data mapping can ripple throughout your organization, leading to replicated errors, and ultimately, to inaccurate analysis.
Nearly every enterprise will, at some point, move data between systems. And different systems store similar data in different ways. So to move and consolidate data for analysis or other tasks, a roadmap is needed to ensure the data gets to its destination accurately.
For processes like data integration, data migration, data warehouse automation, data synchronization, automated data extraction, or other data management projects, quality in data mapping will determine the quality of the data to be analyzed for insights.
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Understanding data mapping for the modern enterprise
Excel Meaning
Data mappingis the process of matching fields from one database to another. It's the first step to facilitate data migration, data integration, and other data management tasks.
Before data can be analyzed for business insights, it must be homogenized in a way that makes it accessible to decision makers. Data now comes from many sources, and each source can define similar data points in different ways. For example, the state field in a source system may show Illinois as 'Illinois,' but the destination may store it as 'IL.'
Data mapping bridges the differences between two systems, or data models, so that when data is moved from a source, it is accurate and usable at the destination.
Data mapping has been a common business function for some time, but as the amount of data and sources increase, the process of data mapping has become more complex, requiring automated tools to make it feasible for large data sets.
Data mapping is the key to data management
Data mapping is an essential part of many data management processes. If not properly mapped, data may become corrupted as it moves to its destination. Quality in data mapping is key in getting the most out of your data in data migrations, integrations, transformations, and in populating a data warehouse.
Data migration
Data migrationis the process of moving data from one system to another as a one-time event. Generally, this is data that doesn't change over time. After the migration, the destination is the new source of migrated data, and the original source is retired. Data mapping supports the migration process by mapping source fields to destination fields.
Data integration
Data integration is an ongoing process of regularly moving data from one system to another. The integration can be scheduled, such as quarterly or monthly, or can be triggered by an event. Data is stored and maintained at both the source and destination. Like data migration, data maps for integrations match source fields with destination fields.
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Text Data Definition In Excel
Data transformation
Data transformation is the process of converting data from a source format to a destination format. This can include cleansing data by changing data types, deleting nulls or duplicates, aggregating data, enriching the data, or other transformations. For example, 'Illinois' can be transformed to 'IL' to match the destination format. These transformation formulas are part of the data map. As data is moved, the data map uses the transformation formulas to get the data in the correct format for analysis.
Data warehousing
If the goal is to pool data into one source for analysis or other tasks, it is generally pooled in a data warehouse. When you run a query, a report, or do analysis, the data comes from the warehouse. Data in the warehouse is already migrated, integrated, and transformed. Data mapping ensures that as data comes into the warehouse, it gets to its destination the way it was intended.
What are the steps of data mapping?
- Step 1: Define — Define the data to be moved, including the tables, the fields within each table, and the format of the field after it's moved. For data integrations, the frequency of data transfer is also defined.
- Step 2: Map the Data — Match source fields to destination fields.
- Step 3: Transformation — If a field requires transformation, the transformation formula or rule is coded.
- Step 4: Test — Using a test system and sample data from the source, run the transfer to see how it works and make adjustments as necessary.
- Step 5: Deploy — Once it's determined that the data transformation is working as planned, schedule a migration or integration go-live event.
- Step 6: Maintain and Update — For ongoing data integration, the data map is a living entity that will require updates and changes as new data sources are added, as data sources change, or as requirements at the destination change.
How the right data mapping tool can help
Advanced cloud-based data mapping and transformation tools can help enterprises get more out of their data without stretching the budget. This data mapping example shows data fields being mapped from the source to a destination.
In the past, organizations documented data mappings on paper, which was sufficient at the time. But the landscape has become much more complex. With more data, more mappings, and constant changes, paper-based systems can't keep pace. They lack transparency and don't track the inevitable changes in the data models. Mapping by hand also means coding transformations by hand, which is time consuming and fraught with error.
Transparency for analysts and architects
Since data quality is important, data analysts and architects need a precise, real time view of the data at its source and destination. Data mapping tools provide a common view into the data structures being mapped so that analysts and architects can all see the data content, flow, and transformations.
Optimization of complex formats
With so much data streaming from diverse sources, data compatibility becomes a potential problem. Good data mapping tools streamline the transformation processby providing built-in tools to ensure the accurate transformation of complex formats, which saves time and reduces the possibility of human error.
Fewer challenges for changing data models
Data maps are not a one-and-done deal. Changes in data standards, reporting requirements, and systemsmean that maps need maintenance. With a cloud-based data mapping tool, stakeholders no longer run the risk of losing documentation about changes. Good data mapping tools allow users to track the impact of changes as maps are updated. Data mapping tools also allow users to reuse maps, so you don't have to start from scratch each time.
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What to look for in a data mapping tool
Cloud-based data mapping software tools are fast, flexible, and scalable, and are built to handle demanding mapping needs without stretching the budget. While the features and functionality of a data mapping tool is dependent on the organization's needs, there are some common must-haves to look for.
Wide format support
Most tools support basic file types such as Excel, delimited text files, XML, JSON, EBCDIC, and others. Look for a tool that handles common formats in your environment, such as SQL Server, Sybase, Oracle, DB2, or other formats. A good mapping tool will also handle enterprise software such as SAP, SAS, Marketo, Microsoft CRM, or SugarCRM, or data from cloud services such as Salesforce or Database.com.
Intuitive and automated
An intuitive, cloud-based tool is designed to automate repetitive tasks to save time, tedium, and the risk of human error. Look for drag and drop functionality that allows users to quickly match fields and apply built-in transformation, so no coding is required.
Workflow and scheduling
To round out automation capabilities, look for a tool that can create a complete mapping workflow with the ability to schedule mapping jobs triggered by the calendar or an event.
Enterprise data mapping for better data management
Data mapping is an essential part of ensuring that in the process of moving data from a source to a destination, data accuracy is maintained. Good data mapping ensures good data quality in the data warehouse.
You can leverage all the cloud has to offer and put more data to work with an end-to-end solution for data integration and management. From connecting the broadest set of data sources and platforms to intuitive self-service data access, Talend Data Fabric is a unified suite of appsthat helps you manage all your enterprise data in one environment. Try Talend Data Fabric today.
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Data Marker In Excel Definition
Office 365 ProPlus is being renamed to Microsoft 365 Apps for enterprise. For more information about this change, read this blog post.
Summary
In Microsoft Excel, you may have a named range that must be extended to include new information. This article describes a method to create a dynamic defined name.
Note
The method in this article assumes that there are no more than 200 rows of data. You can revise the defined names so that they use the appropriate number and reflect the maximum number of rows.
How to use the OFFSET formula with a defined name
To do this, follow these steps, as appropriate for the version of Excel that you are running.
Microsoft Office Excel 2007, Microsoft Excel 2010 and Microsoft Excel 2013
In a new worksheet, enter the following data.
Number A B 1 Month Sales 2 Jan 10 3 Feb 20 4 Mar 30 Click the Formulas tab.
In the Defined Names group, click Name Manager.
Click New.
In the Name box, type Date.
In the Refers to box, type the following text, and then click OK:
=OFFSET($A$2,0,0,COUNTA($A$2:$A$200),1)
Click New.
Amazon s3 scp. In the Name box, typeSales.
In the Refers to box, type the following text, and then click OK:
=OFFSET($B$2,0,0,COUNT($B$2:$B$200),1)
Click Close.
Clear cell B2, and then type the following formula:
=RAND()*0+10
Note
In this formula, COUNT is used for a column of numbers. COUNTA is used for a column of text values.
This formula uses the volatile RAND function. This formula automatically updates the OFFSET formula that is used in the defined name 'Sales' when you enter new data in column B. The value 10 is used in this formula because 10 is the original value of cell B2.
Data Source In Excel Definition
Microsoft Office Excel 2003
In a new worksheet, enter the following data:
Number A B 1 Month Sales 2 Jan 10 3 Feb 20 4 Mar 30 On the Insert menu, point toName, and then click Define.
In the Names in workbook box, typeDate.
In the Refers to box, type the following text, and then click OK:
=OFFSET($A$2,0,0,COUNTA($A$2:$A$200),1).
Click Add.
In the Names in workbook box, type Sales.
In the Refers to box, type the following text, and then click Add:
=OFFSET($B$2,0,0,COUNT($B$2:$B$200),1)
Click OK.
Clear cell B2, and then type the following formula:
=RAND()*0+10
Note
In this formula, COUNT is used for a column of numbers. COUNTA is used for a column of text values.
This formula uses the volatile RAND function. This formula automatically updates the OFFSET formula that is used in the defined name 'Sales' when you enter new data in column B. The value 10 is used in this formula because 10 is the original value of cell B2.
