Big data for social impact

Big data is a hot topic but how we can use the data for social impact? This article in DevEx, “Solving the data conundrum: How to leverage tech and ‘big data’ for impact” brings to light how social impact organizations can benefit and help their organization with the big data challenge.

For example, humanitarian data is important but the insights from the data need to be accessed and gleaned in real-time rather than at a future date. Time is crucial so having access to data such as how much funding organizations are receiving can help others understand the necessity of giving to needed projects.

Some key suggestions from the article provides a few guidelines:

  1. Learn how to ask the right questions
  2. Have clearly defined goals

These two points can be applied to any organization/business but it is just as important for social impact organizations. Why? The goal will help you ask the questions about what data is needed or what is being done to help certain countries who need funding for building schools or relief aid.

Some other key tips include: building effective and easy to use technology platform and collaborating to ensure that data collection and storage is streamlined. Many tech companies are building real time analytics dashboards to allow their customers to extract data quickly to drive decisions. The same applies to social impact organizations; people need to be empowered to quickly access anytime and anywhere the data.

However, this can only happen when all organization stakeholders agree upon how data is collected and stored. The best way to do this strategically and effectively is to bring key individuals together and come up with a plan to implement data collection and storage and communicate it to all individuals with access.

Big data is a crucial source of information for all organizations and empowering people to understand its role, its purpose and how it’s being used can help streamline the efforts for maximum impact.


Big data continues to dominate higher education

In my previous post, I talked about opportunities for higher education leaders to tackle big data challenges. A recent article highlighted how University of Nevada Las Vegas is taking on the issue with the creation of the Institute for Big Data. This is exciting for the institution as they recognize the need to be ahead of the game when they are behind.

With this institute, the institution aims to utilize the data to prepare students for the workforce teaching them the many uses of the data. Some researchers at UNLV have already used this data approach by studying aspects of fracking or even in medical research.

Teaching students the skills to analyze data could lead to more trained data professionals that can run insights and make predictions useful for local businesses. This can fill the gap in local areas and teach students useful skills that can be applied to any industry and job.

With the growing need for data scientists, adding a program and track at colleges to prepare students for the workforce is crucial and strategic. It provides a direct career path for students and key skills for many job prospects or personal projects. This will help prospective students make an early decision about major and career that could save them time and money.


Potential for big data in higher education

Big data has been widely discussed as a way to understand data beyond general insights and into more advanced.

Colleges are a crucial place for student learning and development and with the amount of press devoted to student debt, access to college and attrition, the question is what are we doing with our data? We hear words like assessment and accountability and the understanding of the data is mostly descriptive – let’s take this opportunity to challenge ourselves further with the data.

Predictive analytics and machine learning has been widely successful in cracking down on crime, credit fraud as well as predicting the movies we’d like to watch on Netflix.

Here are some ideas higher education can use data science to support the initiatives and shape the student experience:

  1. Using admissions data of enrolled students and their academic record to predict attrition and retention
    1. Much talk has been about grades, test scores that do not validate a student’s success but can we use the data to track students in academic difficulty? Maybe this might allow us to offer additional services and tutoring.
  2. Using predictive analytics in improving student learning and classes students might be interested in teaching
    1. Using the existing data in a curriculum about the method and style of teaching, faculty teaching experience, class size, grades on different assessments to determine whether the class is going to be successful in their current form or
  3. Amount of debt: income ratio upon graduation
    1. Using student’s financial aid profile to examine patterns between income and amount of student loans
      1. The data might help us identify potential students at risk for significant debt and help students understand how much loans they really need for more financial responsibility.

Here are some additional resources on ways to use data science for higher education:



How big data can hurt civil rights

There has been a lot praise and benefits to the way big data can improve our lives, sleep, the movie suggestions on our Netflix account but on the issue of civil rights big data’s role can lead to a step backward and not forward.

This article  titled “White House: Done wrong, big data can hurt civil rights” sums it up pretty accurately in that big data if used and and shared with the community can be useful; however if we misuse big data then we can hurt the relationships built. Let’s look closer at crime data; big data can be used to understand crime data patterns to see if resources can be better allocated to certain areas.  This information can be shared so people can see what the results of the allocation of resources have led to and the benefits to their community. The key is that the data should be shared for transparency and accountability.

However,the dark side of big data when misused can lead to profiling and targeting of individuals whose credit history, loan information are used against them. While big data can predict which individuals may default on a loan or credit card payment, the information can prevent someone from starting fresh. The goal is not to target people but to use the information wisely and carefully.

Ultimately, big data is here to stay in all aspects of our lives and community. The goal is to share and be open about the data, methods of collection and how it’s being used so that the transparency brings understanding and not confusion or anger.

Fashion and Technology -emerging area of big data?

We all know wearable technology is popular with FitBit and similar devices created to help us track our sleep, fitness, caloric intake and more. Fashion has caught on to the big data trend, specifically Marchesa’s partnership with IBM Watson for this year’s Met Gala. The article which doesn’t use the term ‘big data’ has it written all over it though.

For one, IBM Watson is an analytics tool; so in collaborating with a designer to design a dress there is data being utilized in the design and when the individual wears it to the Gala.

This is great for both IBM and Marchesa for exploring and setting a pattern for new partnerships that benefits both parties. IBM benefits because they are able to test how effective Watson is at capturing the details of a dress that resonates with the public and fashion critics. For Marchesa, the partnership represents a trend towards embracing more utilization of big data and enhances their brand. So a win win on the marketing, business and product and might set off another wave of collaboration between analytics and fashion.

The dress, a “cognitive dress” is smart technology because it incorporates past designs and celebrities who have worn Marchesa to the event that clues Watson into the the human emotions behind the color. As a result, the back end technology runs some algorithm to determine what the dress should look like to reflect the human connection.

The tool and dress design continues to utilize analytics and data in the selection of the material through a combination of “keyword extraction, concept tagging, taxonomy, sentiment analysis, relationship extraction, linked data and entity extraction.” This information is helping to deliver the final product – a dress which will have LED lights that changes colors based on social media response on Twitter.  The LED technology isn’t new – Taylor Swift once gave out LED bracelets to all her concert attendees that track individual’s responses to songs, emotions and more that help her deliver a better concert experience.

Finally, the celebrity wearing the dress will benefit from the data and enhance their own profile by leading the way with new technology trends in fashion. Their own social profile will increase greatly and the data will determine whether they are a great person to wear Marchesa.

Big data is becoming more widespread and necessary, the partnership with IBM and Marchesa can be an opportunity for more companies to explore these partnerships. Ultimately the data will yield valuable insights about emotions, brand loyalty, responses to a dress that can generate more press and revenue over time. When the event is over, it will be fascinating to see what kind of data IBM releases about the dress and read the responses to determine whether the data yielded the potential benefits of the collaboration.


Making Big data more nurturing than creepy

Big data is a hot topic these days from predictive insights such as the next movie blockbuster, hit single and or when a person is pregnant but let’s discuss and explore big data as nurturing than creepy.

This article really caught my eye, Less Big Brother More Big Mother: Three Ways To Use Big Data To Enhance Customer Experience as they give case studies of how the nurture is demonstrated in different companies. Starbucks, Amazon and Stitch Fix are all examples of how you can bring the nurture to the customer experience. Stitch Fix sends you clothes based on your budget and style, you return the clothes you don’t want. This helps them understand your preferences and tailor your next shipment accordingly to meet your needs as a customer.

Starbucks is another example of being ahead of the curve with adopting mobile payments. They adopted pay by phone early on when recognizing how busy their stores can get and a system to sync the customer’s purchases and the gold stars in one transaction.

These examples highlight examples of how to integrate big data with the customer experience to humanize the approach. We need to remember the goal is to better serve our customers for retention and loyalty and grow our brand.

Data analytics a business, not technology issue

The title comes from this Forbes article  where CIOS are talking about big data as a business issue rather than technology issue. This is another great discussion related to big data; most of the time articles are discussing tools and the amount of data but let’s look at the business side for a minute.

The task of gleaning insights and value from data “requires new hybrid teams and roles that understand the business, as well as how and where to find the data that creates competitive advantage.” Big data for many businesses has long been the responsibility of the IT team, however that idea is limited now as the people working on gleaning insights will have input into the data storage as well as leaders/executives who may have a different perspective too. Therefore, the hybrid team makes sense so that all stakeholders can share their input into the process.

Also, as more and more individuals on teams will need access to the data, transferring storage to a cloud based platform makes more sense. Ultimately though, a decision on data storage and analytics will depend on the organization’s size, the amount of data collected and future needs as well as goals.