From adapting energy use to maximizing data consolidation, Big Data (BD) analytics has taken the guesswork out of optimizing the modern data center.
More than ever, the modern data center is a living, changing environment, with new technologies coming in, old technologies being cycled out, and evolving energy efficiency strategies to keep it all humming. We have to make sure we have the space and power to install the latest technology, while we still have the old equipment in place.
Up until recently, orchestrating this shifting ecosystem was only partially data-driven and the rest was based on gauging changing needs from past experience. At EMC IT—like most IT organizations—we had long tracked metrics on our data center facilities, including space, power, cooling, humidity, temperature, etc. And we collected storage data—server utilization, virtual machines, growth trends. But we lacked the tools to process this vast amount of data and we were never able to aggregate this information into one data base.
Converged infrastructure (CI)—pre-engineered and deeply integrated blocks of compute, storage and network that deliver mission-critical performance offered as a turnkey solution—has been a game changer in helping IT keep pace with rapidly evolving business demands. And now a more agile technological cousin, called hyper-converged infrastructure (HCI), offers similar plug-and-play efficiencies using building blocks in smaller, more flexible chunks.
So when should you use converged infrastructure and when is hyper-converged technology a better option? The answer depends on what IT workloads you are running, how much resiliency is required, and the need for guaranteed performance verses agility and scalability.
The data lake is proving to be a crucial tool as EMC IT strives to partner more closely with the business clients it serves to help them get the most out of enterprise Big Data. For example, EMC IT is offering a smart data base that lets business users across the company leverage a uniform customer profile for more efficient and effective sales analytics.
Created in collaboration with EMC Global Services, the CAP (Customer Account Profile) is based on information collected and aggregated from multiple sources to provide a holistic customer view—a single version of the truth, if you will, about our customers.
CAP is managed by IT and is one of the enterprise data sets made available via the data lake to business clients seeking to analyze customer trends, opportunities and insights.
Wouldn’t it be great if you could analyze all customer interaction and learn which parts of our services or sales are better than others? Or analyze all of our service request textual descriptions and infer the call volume drivers? Understand the main topics of a chat session? Use the same data to understand how the customers are actually using our products? Or to go beyond customer interactions and help us identify the common bugs in our code by analyzing the text engineers type in a bug tracking system such as Jira or Bugzilla?
Liberating your data is not enough if a big chunk of it remains locked in human generated texts.
EMC’s Data Science as a Service team has created a highly-advanced text analytics technology which can help your organization unlock the value in human generated texts.
The Business Data Lake(BDL) is positioned as the one-stop-shop for all of the organization’s (big) data storage and analytics requirements. It is intended to address the three V’s of Big Data analytics – Volume, Variety and Velocity – by providing a vast amount of storage, ingestion of streaming, mini-batches and batches of data, either structured, semi-structured or unstructured. It fundamentally shifts the paradigm in business data storage and analytics by consolidating the multiple silos of data that can be found in organizations today.
Viktor Mayer-Schonberger and Kenneth Cukier, authors of Big Data: A Revolution That Will Transform How We Live, Work and Think, wrote, “If big data teaches us anything, it is that just acting better, making improvements – without deeper understanding – is often good enough.”
EMC IT not only recognizes the hidden value of Big Data, but also strives to generate better outcomes. So, we at EMC IT can act better and faster to improve our customers’ experience.
In his November 2013article, Dan Inbar from EMC’s IT organization eloquently presented what IT has been doing to improve the operations of our Exchange email environment. PAITO (Predictive Analytics for IT Operations) is our Big Data analytics solution for outage prediction that allows our IT operations team to collect, analyze, store, and leverage key indicators to predict and prevent interruption in mission-critical operations. The journey that started more than a year ago as a pilot has evolved into a full-fledged IT data lake and analytics platform for various IT managed areas, including applications, servers, devices, licenses, network, storage, security and workloads. (more…)
The 2014 EMC Digital UniverseStudy, with research and analysis by IDC, predicts that by 2020 the digital universe will contain nearly as many digital bits as there are stars in the universe.
According to the study, digital growth “is doubling in size every two years and by 2020, the digital universe—the data we create and copy annually—will reach 44 zettabytes, or 44 trillion gigabytes.”
As companies brace for this data tsunami, they are challenged to identify the next business opportunity, improve risk management, customer engagement and sustainability. They will need to become “predictive enterprises” which leverage their data to define their future focus and how to get there. Sifting massive amounts of data to find relevant insights for business will be a continuous process, constantly evolving and adapting to business climate. IT departments need to have a robust framework to manage their organizations’ ambitions and goals.
IT Proven allows you to leverage EMC IT’s first-hand knowledge and best practices to accelerate your own IT transformation journeys, transforming operations and delivering IT as a Service through the power of cloud computing. IT Proven highlights how EMC IT transformed into an agile, innovative, and competitive service provider.
Transforming an IT organization is a complex, multi-faceted journey that requires new ways of thinking, analysis and structure. With the industry changing at a break-neck pace, the need has never been greater to assume an IT as a Service (ITaaS) model and become a true service provider to the business. To help organizations with their transformations, EMC IT Proven engages customers so they may leverage EMC IT’s first-hand experience to accelerate their own IT transformation journeys.
That is why EMC IT experts will be hosting five LIVE Virtual CrowdChat events during EMC World this year which can be attended virtually from anywhere in the world! (more…)
If your organization is like most, you have multiple business groups seeking to leverage pools of segmented Big Data in various ways to improve their operations, gain insight into customers, target marketing efforts, hone product features and more. Maybe you are even one of the few who have gained some significant value from these siloed business analytics using increasingly popular data science techniques.
However, most organizations, including EMC, still have a way to go to become an analytical enterprise, which bases both tactical and strategic decisions on data and analytics. This does not mean that the decision-making is out of the hands of the leadership of the company and the years of experience they bring, but it does mean that every decision has been critiqued based on what your analysis is telling you.
Project: Root cause analysis of difference in support hours
ROI: Model suggests saving of 500-1,000 support hours on average weekly (up to $5M annually)
I have recently made the transition from academic neuroscience to becoming a member of the Data-Science-as-a-Service team in EMC’s IT organization. The change from academia to the business world is far from trivial. Coming from a computational neuroscience lab, where most of the work involved developing probabilistic models for the activity of neural populations, simulations and implementations were not a top priority. As a data scientist with a mostly theoretical background, coping with implementation, let alone implementation in a Big Data environment, is challenging.
Lucky for me, the change of scientific domains underlying the two disciplines is not as large a “leap” as it may seem at first. When you think about predictive analytics, what is more natural than to think of our brain as a complicated learning machine whose main goal is data compression and interpretation?
The opinions and interests expressed on Dell EMC employee blogs are the employees' own and do not necessarily represent Dell EMC's positions, strategies or views. Dell EMC makes no representation or warranties about employee blogs or the accuracy or reliability of such blogs. When you access employee blogs, even though they may contain the Dell EMC logo and content regarding Dell EMC products and services, employee blogs are independent of Dell EMC and Dell EMC does not control their content or operation. In addition, a link to a blog does not mean that EMC endorses that blog or has responsibility for its content or use.