7 serious mistakes on enterprise data management

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From the lazy to the desire to be proud, many businesses have sinned against the data.Here’s what to look for and how to move from data character to data saint.

 

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Anyone who joins in the big data knows the challenges that businesses face when it comes to the amount of data that is outweighed by normal management.When it needs to be repaired, tame and competitive, meet the expectations of customers and increasingly obey the law most stringently.

While we are in the process of integrating and managing the ‘Wild West’ data – not even knowing who owns the second created data – it is not surprising that some CIOs and board members Decision-based IT is not entirely driven by sustainable ideals.So here they are – seven deadly sins of enterprise data management:

Lust

It’s easy to be influenced by the glamor of shiny things – a new gadget, the latest hi-tech installation, a virtual reality gimmick. But using the budget to paint a nice veneer on top of your system without having to deal with your underlying data while it is active and the connection will cause you many unwanted problems as no what is absolute. Beacons is a great example – many retailers are attracted by the way they can track customer motions anytime they want for their purposes. But in addition, very few people have strategies really to use and manage information safely.

mistakes on enterprise data management

Gluttony

When you know you need to do something about the data but you do not know what it is, it will appeal to everything – introduce new systems and packets on old processes and apply a ‘much’ attitude than’. This may be a note through quick investigations, rather than undergoing too much risk analysis, analysis and assimilation – but often leads to ‘all data, not details’. Additional information is not used unless it can be put into formal operation, which means getting the information exchange system and ensuring you have the proper tools to analyze the data in the process in maintaining your equipment.

Greed

Although data ownership data printing is still being written, wanting to keep and protect your data is not a bad thing. But when it comes to the cost of a business opportunity, greed is too bad for something of its own. If you do not want to share information with proven third parties and platforms that have the potential to make your business better, it can scare away the enemy.

Sloth

May be the worst mistake in all.An incredible number of businesses should know better have decided to solve data problems by burying their heads in the sand and hoping it will go away – for example, according to a vendor study translation.Calligo cloud, 69% of IT decision makers do not have the support for GDPR compliance. After all, the hard job is to build a good data management strategy, in the future – if everything is ticking, although not as effective, what is the worst thing that can happen? The answer is bankruptcy or prosecution when things are out of control.

Angry

Existing businesses will have inherited systems that they are very happy with – they want to continue doing things they have always done. Inertia is a powerful force – business tables will get angry if they are created to break free of their boundaries, beyond their original purpose.And the decisions made in anger over important business strategies will be impractical or permanent when there are risks.

Jealous

“I want what they have” can be heard in the meeting room everywhere – once a competitor acts, there is a scramble to catch up. But knee-jerk reactions make decisions and rushes often become costly mistakes. There is no data management solution that fits all your desires immediately – you need to find out what you want for your brand, customer, sales person as well as what you need for your business before you commit to this platforminstall and change according to all wishes.

Proud

While others bury their heads in the sand or worry about too many competitors, some businesses will think “we have had this nail” – a dangerous assumption.Even the most valued data scientists can not know everything – because data points multiply, so systems, platforms and connections have no way of predicting it all. And, when it comes to law like the GDPR, where the requirement is not clear, it is important to accept that the approach you start with needs adaptation and development – record your decisions and justifications but be prepared. Changes as best practices become clear and appropriate for emerging requirements

  And preparing for the exchange is the only way to avoid trouble.

There are seven serious errors and seven ways of thinking in the overall process, each of which has the potential to interfere with progress when it comes to data management. Fortunately, there is a simple and effective saving method that can help IT strategists go in the right direction. As soon as you start an honest conversation about what you have, what you need and somehow narrow the gap, you can quickly improve yourself against data errors.

 

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