The,connection,between,data,Ha technology The connection between data in Hadoop and advanced analytics


Active shredder safety technology for the small office. Shreds 15sheets per pass into 5/32" x 1-1/2" cross-cut particles (Security Level3). Patented SafeSense® Technology stops shredding when hands touch thepaper opening. Designated shredde The electronic cigarette is not new. People who buy electronic cigarette knows that this product has been in the market for years now. Despite some sectors apparently trying to shoot the product down from the shelves, the popularity of elect


Normal 0 false false false EN-US X-NONE X-NONE MicrosoftInternetExplorer4 /* Style Definitions */ table.MsoNormalTable{mso-style-name:"Table Normal";mso-tstyle-rowband-size:0;mso-tstyle-colband-size:0;mso-style-noshow:yes;mso-style-priority:99;mso-style-qformat:yes;mso-style-parent:"";mso-padding-alt:0in 5.4pt 0in 5.4pt;mso-para-margin-top:0in;mso-para-margin-right:0in;mso-para-margin-bottom:10.0pt;mso-para-margin-left:0in;line-height:115%;mso-pagination:widow-orphan;font-size:11.0pt;font-family:"Calibri","sans-serif";mso-ascii-font-family:Calibri;mso-ascii-theme-font:minor-latin;mso-hansi-font-family:Calibri;mso-hansi-theme-font:minor-latin;}It is undeniable that a massive amount of data (read:multi-structured data) can be stored in Apache Hadoop. However, when it comesto unlocking so much data, business analysts are often seen looking for easyways to do the needful. Perhaps without any relevant programing skills, theyfind it difficult to analyze the data and transform it into business insights.Not to mention, at times, even the lack of distributed processing skills can actas an obstacle when they are looking forward to have their way with advanced analytics. Nevertheless, ineither of these situations, what is required is a solution that can come inhandy when the business analysts try to access the data in Hadoop in a moredirect manner. Interestingly, there are quite a few solutions that canserve the purpose and help the analysts in deriving business insights. However,in order to identify the right one, they may want to crosscheck if all or atleast some of the following requirements are being duly met: Ease of usage: Most of the times, business analysts have no option but to rely on Hadoop MapReduce jobs, which by all means, are complex as far as their development is concerned. As a matter of fact, until data scientists leverage their expertise and put their understanding of procedural programming to use, developing these jobs can be extremely challenging. Therefore, it is imperative that only an easy-to-use solution is used especially if the complexity is to be avoided. Not so high latency: In fact, the lower the better as any delay is likely to have an impact on the insights that need to be derived through the means of data. Furthermore, if possible, then the analysts must specifically look for a solution that allows them to make the most of their existing business intelligence (read: BI) tools. Of course, if they also get to take advantage of the SQL-MapReduce functions, then probably it can’t get better than this. However, the question remains that why exactly is such asolution required in the first place? As already mentioned, the HadoopMapReduce jobs can be quite complex to deal with (read: develop). Here, it isworth mentioning that these jobs play an important role when it comes toprocessing the data that is stored in the HadoopDistributed File System (HDFS). And obviously, until this data is processedin batch mode, it can be difficult to go any further withadvanced analytics.

The,connection,between,data,Ha

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