Big Data: A Mysterious Giant IT Buzzword

Post written by Niaz T., Senior Solution Architect/SAP BW Consultant at Ideaca. Read more about SAP HANA on her blog: Discover In-memory Technology.

In the world of technology there are a hundred definitions for “Big Data.” It seems confusing to come up with a single definition when there is a lack of standard definition. Like many other terms in technology, Big Data has evolved and matured and so has its definition. Depending on who we ask and what industry/business field they’re in, we will get different definitions. Timo Elliott summarized some of the more popular definitions of Big Data in “7 Definitions of Big Data You Should Know About.”

You may be familiar with three “V’s” or the classic 3V model. However, this original definition does not fully describe the benefits of Big Data. Recently, it has been suggested to add 2 more V’s to the list such as Value and Verification or Veracity which are resulted from “Data Management Practices.” As a BI expert who is been involved in Big Data, my approach is to have a practical definition for my clients by emphasizing the main characteristics of data and purpose of Big Data related to each specific area. I like Gartner’s concise definition. Gartner defined Volume, Velocity and Variety characteristics of information assets as not 3 parts but one part of Big Data definition.

Big data is high-volume, high-velocity and high-variety information asset that demands cost-effective, innovative forms of information processing for enhanced insight and decision making. (Gartner’s definition of big data)

The second part of the definition addresses the challenges we face to take the best of infrastructure and technology capabilities. Usually these types of solutions are expensive and clients expect to have cost effective and appropriate solution to answer their requirement. In my opinion this covers the other V which is related to how we implement Data Management Practices in Big Data Architecture Framework and its Lifecycle Model.

The third part covers the most important part and ultimate goal which is Value. Business value is in the insight to their data and to react to this insight to make better decisions. To have a right vision, it’s important to understand, identify and formulate business problems and objectives knowing practical Big Data solutions are feasible but not easy. So when I define Big Data for my clients, I use Gartner’s definition and explain the journey we need to take together to achieve their goal.

In any Big Data project, I start with BDAF or Big Data Architecture Framework which consists of Data Models, Data Lifecycle, Infrastructure, Analytic tools, Application, Management Operation and Security. One of the key components is having high performance computing storage. Since Big Data technologies are evolving and there more options to be considered, I’m focusing on SAP HANA capabilities which enable us to design practical and more cost effective solutions. HANA could be one part of overall Big Data Architecture Framework but it’s the most essential part. The beauty behind SAP HANA is that it is not just a powerhouse Database but it is a development platform to provide real time platform for both analytics and the transactional systems. It enables us to move beyond traditional data warehousing and spending significant time on data extraction and loading. In addition we’re able to take advantage of hybrid processing to design more advance modeling. Another big advantage of HANA is the capability of integrate it with SAP and non-SAP tools.

So, why am I so excited about it? Looking around I see tons of opportunities and brilliant ideas which could get off the ground with some funding. So far, HANA has been more successful in large enterprises with big budgets and larger IT staff. However I’m also interested to encourage medium size enterprises to see the potential of HANA to provide a solution for their problems. The majority of businesses don’t spend their budget to develop a solution. They are eager to pay to solve a particular problem. Now, our challenge as SAP consultants is to help businesses see this potential and how HANA can address their challenges. The good news is SAP supports by providing test environment and development licenses for promising startups.

Got your attention? Well, just to give you a glimpse, take a look at some of the success stories. In addition there are many many other cases if we look around. For instance, these days many applications capture Geo-location data like trucking company, transportation, etc. it means capturing data every 10 seconds or so from every section, every piece of equipment, every location. This could add up to a Petabyte of data! This is an excellent way to bring insight into data and drive intelligence out of it and have it circulated back to scheduling and movement processes. Another example could be companies needing to mine information from social media regarding to their products and connecting this intelligence back to their back end processes to increase customer engagement and satisfaction.

So, do you have any Big Data Challenge? With some funding, we’re able to provide cost effective and practical solution for your challenge to add value to your business.

Setting expectations with clients

Post written by Steve J, Project Manager at Ideaca

The Oxford Dictionary defines “managing expectations” as: “Seek to prevent disappointment by establishing in advance what can realistically be achieved or delivered by a project, undertaking, course of action, etc.”

Almost every part of our lives is surrounded by expectations, either ones we set for ourselves or ones that were set for us by others. When it comes to consulting and being on a project, every part of the project experience will be influenced by expectations. There will be expectations around the project as a whole, the deliverables, the time and especially the budget. It is the responsibility of the project team and Project Manager to ensure that the client has a clear and accurate understanding at all times. The overall success of any project will be linked to the expectations of the client, the understanding and efforts of the project team and how well these factors align. At the end of a project, the client’s satisfaction with the delivered project will determine its success.

I have worked on a variety of projects, including those with high expectations from the client. In one project the client as a whole had very little technical and user knowledge of the system that we were implementing for them. They were very much involved in the project and took on many tasks. One of the tasks that was completed by the client was the design and layout of the new system. This task was completed before the project team started on the project and with limited knowledge of the system. The designer was able to design the pages to match that of a SharePoint look and feel without any operational knowledge of the system as a whole. The project team was not a part of this design and the client wanted the end result to look and operate the same as they had designed it. When our project team realized this, we had to pivot our work to align with a more customized solution rather than an out of the box implementation as originally expected. Communication and managing expectations became a critical component of this project, especially since the plans and timelines shifted substantially. Working closely with the client, being honest about timelines and budget and reviewing changes before work continued were very important. Our open communication kept the client informed and the project team on the right track to meeting their needs. In conclusion, the client was very happy with the end product and assured us that we had exceeded their expectations.

Through my experience working with a variety of clients in different situations, I have developed an understanding of how to best manage client expectations. As in the example above, the situation could have turned out with one, or both parties upset about the changes in plans. But by effective expectation management, we were able to explain to the client why things needed to change and what exactly we were going to change. This turned a potentially problematic shift in work into a positive improvement of work.

In my next blog entry, I’ll cover the four key factors in managing client expectations that I have learned throughout my career. Check back next Tuesday, September 17 for more!