Guide to Implementing company brain - 2 - Merging and Managing Data

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It is often assumed that a data storage is imperative to any business, ordinarily because It departments don't want to article directly off their source systems and they conclude they need a data warehouse.

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Building a data storage can be a large and precious project so you need to consider what real benefits it could bring to your business, you need to think carefully about why you're doing it and what the purpose is.

Maybe you can article directly off your source system by improving the capacity of that server or that hardware you're using. By duplicating and just reporting off it, you'll very swiftly get administration information out to habitancy and it might be adequate, further more, by doing this you'll learn your data, and understand the pitfalls in it.

This means that you've already solved a lot of the issues and problems if you do conclude to build a data storage in the future, so when you out grow reporting directly off your execution systems you can then evolve quite categorically because you now have more knowledge into building a data warehouse.

One of the biggest challenges you're likely to face with firm intelligence when it comes to ensuring you merge prospective customers is development sure your data is merged and collated to give you the right information at the right time. Your buyer association administration (Crm) system may know who your customers are, but it might not know when one of your customers transacts with you.

This can come to be even more problematic if you have any transactional systems and channels to market. For example, if you were to take a football club that may have it's season mark holders, then turn style mark holders and a shop. You may not know that a buyer brought something from the shop even though they've got a season ticket, so you'd use a data storage to pull all that data together giving you a single view of the buyer that can be sent to the Crm explication and the marketing campaign can be targeted accordingly.

The question often lies in ensuring the Crm doesn't already have that information and duplicating it, as most Crm systems will include double data anyway (with distinct titles, names, addresses etc), you need to ensure the tools you are using can integrate that data effectively from the data storage into the Crm explication and vise versa as the data comes back.

Another major obstacle your firm may encounter when implementing a firm intelligence explication is user adoption - getting your staff to actively analyse the data you're producing and using the data gathered.

Just because the It branch has brought some new tools, doesn't mean the rest of your staff are going to use them, they might not have the time, they might not see the benefit to them or they plainly may not understand it. This means as part of implementing a new Bi solution, you need to understand your users and deliver the information to them in a way that's going to make them want to use it too. This needs to be looked at on an ongoing basis, you need to all the time be aware of what's being used and what isn't, if it's not being used you need to know why, if it's plainly a case of staff not having the time or insight it, you need to invest the resources to rectify this, or if it's categorically not working you'll need to find an alternative solution. Once your users see this technology can make their job easier, you'll start to see the value in your investment.

This all the time works from the opposite perspective too, if one of your users are told any requests will take any weeks or months to action, they will soon stop asking and the technology wont be being used to it's full potential.

Data ability will all the time cause risk because you're pulling data from any systems and from any years and this means the chances are the data has been captured in distinct ways.

There are any steps you can take to ensure the risk is as minimal as potential beginning with exposing the data to the end user as soon as potential because it's their data and it's them who are going to be able to conclude whether the data is right or wrong.

There are fullness of data ability tools that can help when it comes to automating and cleansing the data that's been gathered. These tools can help merge and de-dupe the data and they can use fuzzy look up logic and look up to catalogues. If you have units of determination across your stock range, these units can be standardized and converted to clean your data automatically.

The main challenge here is development sure all the data is standardized and documented as soon as possible. The distinct firm rules are documented and shared and this all falls under the umbrella of a data governance programme to be managed, coordinated, and governed.

In most companies it will be the finance branch that looks after the planning and budgeting using Excel, meaning it's done exterior the core It systems. The planning and budgeting is a key part of your information administration straight through monthly or regular forecasting which is often feed into the administration information systems.

These two systems ideally should both be incorporated into the firm intelligence explication because it's a key input. This means the data warehousing, firm intelligence reporting process, month end reporting and planning and budgeting are categorically interlinked and as such you need to buildings your programme and you firm intelligence deployments taking them into account.

When we're doing data warehousing and pulling data from many sources, you often have the same data advent from multiple systems causing issues with duplication and inconsistencies. The data quality, buyer data or stock data often has to be merged into a scholar set, often the data storage becomes the scholar data administration product. It's often ideal if you can administrate you scholar data, and put it in as part of your data governance programme early on in the project then that will help your Bi deployment later on. This means the your scholar data will be known, you'll know who controls it and the procedures and system around managing it.

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