According to MIT Technology Review, roughly 0.5 percent of digital data is analyzed, which means, nonprofits are losing millions of opportunities to make smart decisions, improve efficiency, & attract new donors and volunteers. The reason is simple; they are not leveraging the potential offered by data analytics.
IT job numbers grew in July, but not as fast as they did during the rest of 2016. Yet big data and cloud trends will continue to drive job growth going forward, according to CompTIA researchers. A new report from CompTIA that analyzes some of this job growth attributes the trend to growing tech areas such as big data and cloud computing.
Stats, facts, and figures—we all love data, and it certainly helps make content all the more powerful. Data, when used properly, makes an argument more compelling, underscores a position, and adds relevancy and authenticity to a story.
Yet we’ve all seen infographics, slides, and blog posts so cluttered with a hodgepodge of complex charts and figures, they actually depreciate the effectiveness of the content and the message. How do you balance data, design, and messaging to tell a stronger story?
How many times have your donors had the thought: "Is my donation being used efficiently?"
Many nonprofits are storing and analyzing data to improve their own logistics and gain access to a greater number of potential donors right away. By turning to data to make the process of managing fundraising activities and making them more effective, nonprofits are able to become more effective fundraisers and be more transparent with their donation revenue than ever before.
The demand for data scientists, analysts, and big data experts is strong, and educational institutions are scrambling to meet the demand.
Tech Impact's partnership with ZipCode Wilmington, Delaware's first coding school. Teaches students Java coding in a 12-week course, followed by an apprenticeship program that launches new careers immediately upon graduation. Giving students an experience that fast tracks them into a great career, at a great salary, and we do it in under a year.
What is the future of the big data? Whichever way you look at it, there can be only two potential scenarios.
Output one. The data we gather from smart sensors, wearables, and the Internet of things is going to continue to grow. With that, new technologies are going to develop around it.
Output two. The big data becomes a relic as there is always a new trend to come out, like the cognitive technology.
It is time to see what top experts in the field have to say about the future of the big data.
1. Big Data And Analytics Continue To Grow
All experts agree that we are going to continue generating larger volumes of data. If we take into consideration the number of mobile devices and the IoT devices, the big data is going to grow to unprecedented levels.
As the data grows, also the ways to analyse the data are expected to grow and improve. Spark, SQL, and many new tools for analysis are going to emerge and improve.
Machine learning, the cloud and the smart appliances are driving the next wave of big data, with Spark as one of the fastest growing.
Also, big names like Salesforce and Microsoft, are already working on predictive analytics platforms with features that let non-coders create apps to view and work with business data.
2. Big Data, Insights, And Action
Having insights into the data is the way of going forward if you want to win in the big data market. Being able to access, use the data and make decisions in real time is paramount.
There is a gap between insight and action in big data at the moment. However, by the end of 2016, this gap is going to close and all the spent energy around the big data collection is going to redirect towards insights and execution.
“Actionable” of “fast” data is going to replace the big data. Big is is not better when it comes to data. Moreover, most businesses do not use a fraction of the data they collect. Instead, thanks to A.I., the companies are going to focus on asking the right questions for the best “actionable” data.
3. Machine Learning Cleans Big Data
According to Gartner, machine learning is a top trend for 2016. Machine learning is the key element for data preparation and predictive analysis in the businesses of tomorrow.
The next step in “big data” is to create a link between cognitive computing and data analytics. More of less, in the same way that the today’s businesses accept that between the big data and analytics there is a deep connection.
The growing volume of data sources and their complexity of information makes manual analysis uneconomic and infeasible. Thanks to DNNs (deep neural nets) we move beyond classic computing and information management and create systems that can self-learn. Systems able to perceive the world, without human help.
4. No Data, No Business
“By 2020, All businesses are data businesses or no businesses at all.” More and more companies are going to drive value and revenue from their data. All businesses using “correct data” are going to see $430 billion in productivity benefits over the competition not using data.
Businesses are going to purchase algorithms rather than program them and add their data. Existing services like Algorithmia, Data Xu, and Kaggle can be expected to grow and multiply.
5. Privacy And Security
Big data faces major challenges around privacy. The new privacy regulation from the European Union forces companies to address their privacy controls and procedures. By 2018, 50% of the business ethics violations are going to relate to data.
It is true. Only time can tell which of these predictions are going to come true and which are going to pass into obscurity. Regardless, the conclusion here is that the big data is only going to get bigger. More important, the companies that ignore the big data are going to be left behind, to a stopping point.
Over the past few years, "big data" has almost become a household word. From hospitals to classrooms, what was once the business of search engines and financial markets is increasingly affecting every aspect of business and life, and that includes the nonprofit and human services sectors.
So, if you know you’re succeeding at some level and you can see and even count your “impact” with little more than a calculator, why is nonprofit data management important? Why should you consider integrating nonprofit database software into your evaluation and assessment activities?
The power of data has swayed traditional business practices in both for profit and nonprofit organizations alike. In the nonprofit sector, through effectively harnessing, organizing, and subsequently visualizing data and information about donors, organizations are armed with a plethora of new information that they can use to guide their fundraising efforts.
In what seemed like the blink of an eye, the word “big data” dominated the headlines around the world and struck fear in the hearts of CIO’s, nonprofit executives, and the back-office IT guy. What used to be the problem of big technology firms in Silicon Valley quickly became a problem for almost every business, nonprofit, and human services organization alike. And it happened quickly.
Data management can be a tedious, difficult process, but if done right, has the potential to be one of the most rewarding and profitable endeavors in which your nonprofit can engage.