Understanding How To Accelerate Progress In Hadoop Datawarehousing

hadoop data warehousing

IT organizations, sometime or the other realize that data across their corporation isn’t really integrated. And in many companies, the data doesn’t really help them predict the future by actually peeping into the past.

And companies then created spaces for data that is also drawn from the history and typically named the storage spaces as “data warehouse.”  Well this isn’t a fairy tale that ends with a “happily ever after.” This is the true scenario in each of the IT organizations.

When it comes to data integration and warehousing, today, Hadoop datawarehousing is believed to be an excellent platform.

Hadoop Data Warehousing

Let us look into what problems companies face with respect to data integration

  • The first and foremost issues that companies face is with the non-loading of the database technology, integration of the same. This can be countered only by changing the complete design and properly index the database to push it to perform better.
  • You need to work more on the reporting tool technology so as to make it intuitive and write reports to get the right information in reach to the user
  • You need to really program a lot as ETL tools are not always enough to do the job and you may need to quickly pick any software available and get things going.

How To Accelerate Progress?

Hadoop datawarehousing technology demands programmers or developers to really work smartly to make things happen on this space and one of the important things they should do is reporting. The world out there is preparing new tools to sync with Hadoop as we discuss on the progress.

Hadoop datawarehousing should be perceived as a combination of Hadoop and dataware, which are believed to be a great duo for excellent business outcomes.

In this highly competitive world where everything is getting expensive, companies look at certainly cutting costs wherever possible. Actually traditional databases are cost wise lower as compared to Hadoop.

You must choose Hadoop only when you your organization’s big data demands are genuine. However, Hadoop also is cost effective when combined with certain open source software. You may also choose a cloud based Hadoop as it will eliminate the physical server expenses.

Hadoop when combined with dataware will reap eminent outcomes adding value to all the hard work companies pour in to create an efficient Hadoop datawarehousing.


You might like

We use cookies in order to give you the best possible experience on our website. By continuing to use this site, you agree to our use of cookies.