Transamerica – How One Company Is Capitalizing on Big Data Analytics

Companies who want to have continued growth understand a key component of their success will occur when they are able to personalize their customer’s experience, rather than a one-size-fits-all approach. Not only is the personal approach ultimately more efficient for organizations, it also helps increase customer satisfaction, which in turn leads to more growth.

TransamericaOne company, Transamerica, decided to harness big data concepts in order to provide the best possible personal service to its 27 million customer base. Transamerica pulled in data from over 40 sources, including social media, third-party data, customer voice response systems and all its investment, retirement and insurance data sources. By using big data analytics and machine learning concepts, Transamerica was able to identify new data patterns and insights in order to quickly and efficiently develop, test and deploy its predictive models. Now building models takes hours instead of days, allowing for fewer processing cycles and thereby reduced infrastructure demands, while at the same time increasing the personal experience for its customer base.

So what are some of the tools that Transamerica used to accomplish its goals? Transamerica takes advantage of Hadoop, part of the open-source Apache project. By using a Hadoop-based data lake along with a host of other tools, Transamerica found it was able to store vast amounts of data in their distributed computing environment. Of course, security risks are always a factor when dealing with large stores of potentially personal data, so Transamerica’s entire platform was designed in such a way as to maximize appropriate use of data and adherence to legal and regulatory obligations, while minimizing security risks.

Want to know more about how Transamerica and its customers win big with big data analytics? Click here.

Cloud Technologies and Handling Ransomware

Cloud computing is one of the best technologies to have in the workplace. Not only can you store your data quickly and efficiently, but it’s also easier for you to access any data. With that said, when it comes to your business security, especially the malicious tool known as ransomware, why are cloud services so important?

Cloud = Virtual Storage

One reason why, is because cloud computing allows you to store your data virtually over the Internet. This makes it untouchable in the event of a disaster. Let’s say a ransomware attack happened on your device, and it affected the data on your hard drive. Despite this, none of your virtual data would be affected, especially since this isn’t what most hackers are banking on. However, since ransomware locks your computer, you wouldn’t be able to access any of your virtual files, right? As a matter of fact, you can. Cloud computing not only keeps your files safe in the event of a disaster, but your data is also accessible from any device with an Internet connection. Whether it’s another computer in the workplace or even your mobile phone, the sky’s the limit to where you can access your personal data.

For more information about cloud computing, COMMON offers educational opportunities throughout the year. Stay in touch to see when the next cloud-related sessions become available.

IT Education – Preparing for a Career in Data Science

Data Science

Do you love mathematics? Do phrases like “data warehousing” and “v-lookups” bring out the inner nerd in you? If any of this sounds familiar, you might want to steer your direction toward a career in Data Science.

According to Patrick Circelli, a senior recruiter for the IT recruiting firm Mondo, “Data Science is all about mathematics, so having that type of degree — mathematics, information science, computer science, etc. — is especially key for these roles. Hiring managers really love that.” Circelli goes on to describe the must-haves for anyone preparing a resume for a career as a data scientist. His list includes:

  1. A degree in Information Science, Computer Science or Mathematics
  2. Microsoft Excel, specifically the use of pivot tables and v-lookups, and knowledge of SQL queries and stored procedures
  3. Programming skills in any of the following languages: C++, Java, Python, R, or SAS
  4. Concepts such as predictive analysis, visualization and pattern recognition, i.e. understanding how data operates, and skills that could come from data visualization tools like Tableau
  5. NoSQL database environments like MongoDB, CouchDB or HBase
  6. Data warehousing

Although there are many areas in IT that require data science skills, thanks to relentless cyber attacks, the growth rate in security data science specifically, is booming at 26%, with the security analytics market set to reach $8 billion by the year 2023. Anyone who can create a resume listing Circelli’s recommendations, along with a desire to focus pointedly on data security to combat hackers and cyber attacks, can probably write their own ticket in the tech world for decades to come.

IBM Watson For Oncology Going Live in a U.S. Community Hospital

In a first for the U.S., IBM’s Watson For Oncology (WFO) is essentially joining the clinical staff at an American community hospital. After being trained at the Memorial Sloan Kettering Cancer Center, and being tested in hospitals in several parts of the world, Watson will assist doctors at the 327-bed Jupiter Medical Center of Jupiter, Florida, in developing personalized treatment plans for cancer patients.

Why Watson?

What Watson brings to the table is its ability to quickly sift through reams of data from medical journals, textbooks, and clinical trials in order to provide doctors with rankings of the most appropriate treatment options for a particular patient. Identifying the proper treatment regime for cancer patients has always been difficult. Now, with rapid advancements in cancer research and clinical practice, the amount of data available to doctors is far outstripping their ability to keep up with current best practices.

WFO can lift much of what is essentially an information processing task off the shoulders of physicians. By combining information from the medical literature with the patient’s own records and physicians’ notes, Watson can provide a ranked list of personalized treatment options. And if patient records don’t provide all the information it needs for its analysis, Watson will even prompt the physician for more data.

Humans Still Required

Of course WFO is not intended to in any way replace or supersede human physicians. Dr. Abraham Schwarzberg, chief of oncology at Jupiter, thinks of Watson as providing a “second opinion” in the examination room. Doctors can access Watson’s recommendations on a tablet device while the examination of the patient is in progress. “We want a tool that interacts with physicians on the front end as they are prospectively going into making decisions,” says Dr. Schwarzberg.

Results

HospitalIn a study of 638 breast cancer cases conducted at a hospital in Bengaluru, India, WFO’s treatment recommendations achieved an overall 90 percent rate of agreement with those of a human tumor board. Still, IBM acknowledges that it’s too early to claim that Watson will actually improve outcomes for cancer patients. But with the vastly improved ability to personalize treatment options for individual patients that Watson provides, there’s every reason for optimism. As Nancy Fabozzi, a health analyst at Frost & Sullivan puts it, “Watson for Oncology is fundamentally reshaping how oncologists derive insights that enable the best possible decision making and highest quality patient care.”

IT in Manufacturing: Are You Making Good Use of Your Data?

Recently, The Manufacturer came out with an article on what it means for the manufacturing industry to embrace the digital revolution.

One of the key points is that success depends in large part on how you make use of the data you collect. The article mentions a report showing that roughly 99% of business data gets disregarded or tossed out before any analysis can be performed.

IT in manufacturing should involve helping your company make optimal use of data.

The following are some of the benefits:

  • Important feedback on how your machinery and computer systems are operating – whether or not they’re:
    • Efficient and productive
    • Performing consistently within desired parameters
    • Free from signs of impending malfunctions or unauthorized activity
  • Insights into how you can streamline various operations and processes:
    • Saving you money
    • Connecting different parts of your company seamlessly
    • Reaching your customers in a timely and effective way
  • A stronger basis on which to plan for the future, including:
    • Anticipating what you’ll need down the road
    • Embracing new developments in technology

When it comes to making good use of your data, consider the following:

  • The data you need to collect vs. what you can allow yourself to discard
  • How to collect the data accurately
  • Where to store the data securely and how to keep it organized and well-managed
  • The programs to use for analyzing the data, presenting it comprehensibly, and extracting important insights from it

Data is the foundation on which your manufacturing enterprise rests. Letting it slip by without any meaningful analyses puts you at a disadvantage relative to competitors and causes you to miss out on opportunities to refine your operations and further your business objectives.

Manufacturing

How Predictive Analytics Can Help Businesses Secure Funding and Boost Sales

There are several key factors that contribute to business model success. When businesses are looking for investor financing or when professionals seek to salvage a failing business, they look to see if these factors are in place and working well together.

Once business owners understand what these factors are, they can strengthen any weak areas they find in their business.

Zbig Skiba discussed successful business modeling and the book, Business Model Generation, in a LinkedIn article.

The 9 key elements of a good business model the book outlined were:

  • Knowledge of your customer segment and, “distinct target market;” people with similar desires and needs and the ability to pay for your product or service.
  • Your unique value proposition. What does your single product or service or bundle of products and services offer your customer segment?
  • Having efficient channels. Channels are the way you communicate with your customers. There are sales channels, delivery channels, follow-up channels etc.
  • Customer relationships. What is your experience and interaction with your clients? Are they satisfied with your business?
  • Revenue Streams, money coming in.
  • Key Activities, things you must do to conduct business every day. These might include manufacturing and design, etc.
  • Key Resources, your staff, financial resources, physical and intellectual property etc.
  • Key Partnerships, your vendor relationships and partnerships that make your business better, more affordable and more efficient; and
  • Your Cost Structure, the money you have to spend to run your business, including payroll, loan payments, raw materials, delivery costs, licensing fees and rent etc.

Many business owners and managers have yet to learn that comprehensive data analysis or predictive analytics can help strengthen weak areas in their business models.

How?

  1. Predictive analytics organizes big data. This helps businesses clearly see what their target market needs, wants and can afford to pay for.
  2. Once business owners and managers understand their target market at this level, their value proposition becomes clearer.
  3. Businesses can then start using communication and delivery channels that are convenient to their best prospects and therefore the most effective.
  4. Customers feel heard when businesses meet their needs and provide the products and services they desire. Satisfied customers turn into long-term clients and brand advocates.

Predictive analytics can also boost sales by helping businesses:

  • Identify their best revenue streams
  • Understand what activities they should continue and which ones to stop
  • Know which employees are right for each job
  • Know which vendors to partner with to satisfy their target market better
  • Budget more efficiently and stop wasting money on expenses they don’t need