MSP Databalance Case Study: Business decisions in real time based on fast data-driven Analytics

In our modern datacenters, we prefer IBM infrastructure. For our environment we have a mixed platform from Intel, Linux, Power i and AIX.
For this we use the various IBM Power P, Power i and Intel servers. All these systems are linked using the capabilities of the IBM San Volume Controller, FlashSystem V840 and V7000. As central storage solutions we use the V3700, V7000 and V840 storage systems, because of their excellent speed, reliability and low operating costs. The San Volume Controller is used to easy tier, real time compression and mirroring. With these standard techniques present at our systems we are redundant and thus high available. To insure continuity, we are using Tivoli Storage Manager software on most platforms, fully integrated with our SVC solutions. Together with IBM we can offer all possible cloud solutions for our customers, IAAS, PAAS, SAAS. The SAP platform used by Beeztees is hosted by Databalance Services. Databalance advised Beeztees to put the database servers on IBM Flash Storage. This IBM V840 Flash Storage delivers more than 400 thousand IOP’ s. The other servers have been placed on Easy Tier Storage, resulting in an optimal mix of speed and capacity. In practice the generation of reports, lookup jobs and batches are processed much faster. Databalance is a key partner of Beeztees in the field of automation. Throughout the whole migration Databalance has been involved and has advised and supported us. The result of the last months is a very modern and “state of the art” ERP platform based on SAP software and IBM hardware, which enables Beeztees to stay a few steps ahead of the competition. IBM Spectrum is based on software-defined storage and it enables users to obtain increased business benefits from their current storage products whether from IBM or another vendor. IBM has pioneered in this field since 2003 and supports more than 265 storage systems from several brands. This give you more value from earlier storage investments. Databalance is making use of the IBM Spectrum family in serving its clients. The IBM Spectrum Virtualize is a giving maximum flexibility and reliability by virtualizing the storage. You can also get more benefits by using features like Real Time Compression and Easy Tier. And of course you can create a disaster recovery environment by implementing remote mirroring. With IBM Spectrum Protect you enable a reliable, efficient data protection and resiliency for software defined, virtual, physical and cloud environments.

What is Business Analytics?| Career Growth in Business Analytics| Introduction to Business Analytics

Business Analytics in essence is talking about how do you use data how do you use IT and how would you use conceptual layer in business logic to understand how the problem would be resolved right so that in a nutshell would say that this is Business Analytics now you can refer to this as Business Analytics if you make it a little bit longer with some experience nudged into it it would be called as data science right so that in essence would be all about business analytics so I wouldn't restrict this field of study to a specific domain not that an engineer should only do it not that a BSC guy should only do it not that somebody who has come from a Beacom background or commerce background should do it in fact it can be done by anybody I have had students who have come from music from the music industry saying that they like creativity right so if you say that there is creativity in music the same exists in data patterns also right so it doesn't restrict us so anybody can learn it the only thing is that do you have the interest in you do you want to use it for your domain right so the application is varied it can be applied in pharma it can be applied in manufacturing consulting any domain you talk about it it is applicable the one important attribute a person should have is his interest in learning right so you should be somebody who is ready to learn so I wouldn't say although analytics is a complicated subject no doubt about that but I wouldn't say that you should restrict yourself by saying that I don't know IT i don't know statistics I don't understand anything about business so I shouldn't be stepping into this no I wouldn't say that is what stops you what stops you is whether you are ready to learn or not ready to learn right you should be able to adapt you should be ready to let learn you should be able to be agile and understand it right so that is only thing which is required in a student to learn analytic the core structure is with an assumption that a person doesn't know IT it doesn't understand statistics and has never dealt with business case study situations right that's the assumption right eventually people come with one strong background like somebody might be from an IT field is another person might be from a stats field somebody might just be into sales and marketing and he doesn't know anything about statistics or IT right but we can group this person up to a limit which is expected from the course right it's an advantage if you know something but that doesn't stop you from becoming a resource in business analytics that's how you would see it right so nothing is stopping you there is no barrier you just have an advantage you in fact it makes more sense for a student to learn it the reason being that we know that this subject this notion of analytics is obviously coming from the West they're in essence 80 to 90 percent of the work is done using analytics see over here do our jobs by our gut feeling right now corporates and vice presidents of major companies they have started thinking that yes we want to incorporate analytics in every decision we make a person who is just graduating may be doing his engineering college course or maybe he was doing his BAC course or be a become course or maybe even an arts course it makes more sense for him to learn this for a fresher it means that he is getting an edge or existing candidates within his college premises because he knows analytics and others don't know and frankly speaking today most of the engineering colleges and all these guys have started rooming their candidates on some aspect of analytics but the only thing is that it's restricted because of the curriculum which they can be exposed to it's more more of theory and less of practical typical data analysts in the US culture would typically mean a data scientist a short version of a data scientist whose job would be to read patterns into data nevertheless it doesn't mean that he wouldn't be working with data he would start from scratch from extracting data cleaning the data reading patterns out of that making sense out of that pattern and trying to put up the case in front of this know if I have to look at a data scientist specific job description in the Indian market per se it would talk about right from creating a requirement for analytics right because today the market doesn't see a requirement for analytics so you might have a company which is into retail which doesn't think about doing campaign based on the customers buying pattern but just as a campaign which is blanket I would want to customize this according to the requirement of the customer so it's a win-win situation for the company as well as for the customer in this case analytics would help the data scientist can be of great help to the company to reduce the cost of marketing increase the efficiency of marketing and this applies in every domain marketing sales HR right so going forward we can see an application wherein and data scientists would be working along with the HR team to actually analyze which set of employees should be retained for a longer period of time right so this would be some typical things which a data scientist would be doing for the company okay now if you look at a freshers perspective right first if she does some course which is about data science or about business analytics it gives him an edge to the companies when they are recruiting for a marketing professional also would expect that the candidate should know about analytics right today if a company which is in retail is looking at customer analytics they would obviously expect a guy who knows about marketing sales plus analytics they don't want a person who just knows one domain right so it's imperative that you will have to add up all the skills so do you see any cricketer today who can say that I can only Bowl No today we expect that a player should know bowling batting fielding everything which can be done on the field so that is a data scientist he can do excellent presentations he can talk in front of a big crowd he can work with codes he can work with data he understands database it's not that he will manage the database but he is in a situation to guide a database administrator also as to how the database should be for him to work in his favor so that's about the skill set level now from the freshers perspective obviously the first job would not be a very high-paying job but it will be reasonable somewhere around 4 lakhs to file lakhs that that's what you can expect if he is not from a very a great college right obviously if you are from an IIT or something like that or from an ion it gives you an edge it's because of the college brand now initially you will have to work with a lot of data so you will have to work with data you will have to extract data do all the preparation work on the data and present your report later on as you accumulate more knowledge you might get some more additional knowledge about how databases work so today we are talking only about Oracle data scientists might talk about no SQL Hadoop and all those things so he will enrich himself she will be an asset to the company and that is what a data scientist is about and that is what separates him and that is where he creates value for himself I wouldn't quote it to be the next big thing to happen because the next blip or the boom usually is followed by a drop right so this is not going to be followed by a drop this is there to sustain itself for a longer period of time the names might change we might see some more innovation right we are adapting right and we will be adapting more right slowly as we go forward analytics will be a common thing and obviously if it is becoming common thing it's not just a boom it's therefore staying for a longer period of time I would recommend students to take up a course like this irrespective of whether they see a career for themselves in an analytics or not the reason being that going forward no matter what domain you are working in analytics will come in play it will cross paths with you right and at that point in time if you don't know about it it's a problem someone should come to a mess pro school because it has a holistic approach there is a lot of content depth a lot of research has been done before the course has been launched it is followed by a strong examination path so which make sure that the student or the participant has thoroughly understood the subject so we have the NSE certification which comes with this so when you clear that it's an indication that yes you are ready for the industry along with that when you are taking this course but I am is pro school you are doing a practical mix of application along with the theoretical content which is taught in the class right and this gives you an edge over others today when I see a critical combination of something which is creative and analytical is nothing but a data scientist so here we are