Intelligent Data Centres Issue 39 | Page 32

KNOWING WHERE TO GO FOR ACCURATE DATA AND WHEN TO USE IT IS AN IMPORTANT STEP IN IMPROVING DATA MANAGEMENT . historic data and current data to monitor trends , on the surface of it , sounds like it should be straightforward . However , many organisations still struggle with effective data management and data integration .
EDITOR ’ S QUESTION
CHARLES SOUTHWOOD , REGIONAL VP AT DENODO
ew would argue against the assertion that

F the business world is facing more uncertainty and risk than it has in decades . This brings with it unexpected challenges to business models which , in turn , will drive change . It is undoubtedly an opportunity for the most agile businesses , however , it is also exposing the vulnerability of those unable to adapt .

Of course , for a business to perform effectively , it needs meaningful accurate insights . The combination of both

KNOWING WHERE TO GO FOR ACCURATE DATA AND WHEN TO USE IT IS AN IMPORTANT STEP IN IMPROVING DATA MANAGEMENT . historic data and current data to monitor trends , on the surface of it , sounds like it should be straightforward . However , many organisations still struggle with effective data management and data integration .

One challenge they face is around data siloes that may have resulted from the use of legacy systems which weren ’ t designed for integration or from aging disparate storage systems that have either capacity or performance issues . Of course , this is further complicated by our current landscape which includes a mixture of on-premise and newer cloudbased storage models , as well as SaaS application adoption .
When it comes to data , another challenge is that its quality may vary from source to source . For example , a company name taken from a CRM system may not be accurate compared to the same details obtained from the UK Companies House , who will be holding the exact legal entity names of all UK registered businesses . Knowing where to go for accurate data and when to use it is an important step in improving data management .
This is where data virtualisation technologies can help . They can help organisations to combine historic and current datasets to give them the insights they need for the business . By leaving live data at the point of creation , organisations can save huge amounts of data movement and boost agility .
To put this into perspective , as consumers , many of us now enjoy realtime music streaming services like Spotify , Qobuz and Tidal . We no longer have to hold collections of CDs or records in the home . We get what we want , when we want it each time . This is what data virtualisation brings to businesses . Through the abstraction of data , it improves data management and enables real-time access from original sources , only as and when required . It removes the need to move and copy data into physical data marts and eliminates shadow IT . This is better for the business as it provides self-service , and better for IT as it centralises data security and improves data management .
Through improving data management , organisations can ensure that new insights are easier and quicker to determine . They can also address new faster-moving business models and get feedback to allow measurement and refinement . Ultimately , in our new competitive landscape , it will be the businesses that are getting data management right , that prevail . �
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