Purity Mumo, East Africa Philanthropy Network
Big data is an amalgamation of structured, semi-structured and unstructured data collected by organisations and that can be unearthed for information and used in tool learning projects, predictive modelling and other revolutionary analytic applications. Structured data is regularly in a systematised layout, has a clear-cut formation, abides by a data paradigm, follows a purposeful disposition, and is comfortably obtained by people and programs. On the other hand, semi-structured data is never grasped or designed in standard methods. It does not adhere to the composition of tabular data versions or comparative databases owing to the fact that it does not have a fixed outline. Unstructured data is equally never codified in a presumed way, lacks a predetermined data model and therefore, not a good fit for a conventional relational database.(Bridget Botelho & Stephen Bigelow, 2022)
Wayne Thompson 2022, also describes big data as data that is so huge, swift or complex and that is strenuously impossible to process using traditional methods. The act of obtaining and keeping huge volumes of information for analytics has been around for a long time but the notion of big data attained impulse on the onset of the 21st century when veteran Doug Laney expressed with precision the prevailing definition of big data as the three V’s:
Volume – This links with the downright dimensions of the data sets associated with information originating from business deals, smart tools, industrial equipment, social media, and other streams inter-alia, which has made it ordinary to gauge big data with reference to petabytes or exabytes of information and even vast units.
Variety – This serves as a mark of the abundance and diversification of information roots that constitute big data and that stretches from numerical data in traditional databases, through multimedia streams of audio and video, to financial undertakings, text documents, emails, and metadata (information about information).
Velocity – This refers to both the frequency at which fresh details are generated and to the coveted pace for it to be comprehended so as for opportune and apt nuggets to be accessible. This includes input such as computing social media posts and output such as the processing deemed indispensable in executing a process or producing a report.
Data informs a battery of undertakings in every organisation and has indubitably remoulded many fields for the better. It defines the manner in which businesses approach their target groups, how they design fitter products and services, how they alleviate risks, and prolly how they handle their supply networks. Nonetheless, what is the place of big data in the third sector?
In an increasingly data-driven world, civil society organisations would require big data to be more potent in their endeavours as they are customarily oblivious about profit and in lieu, more engrossed in changing the world. Majority generally dawdle in their efforts towards digital transformation, but some have honed-in on data and realised sublime results. Apparently, a comprehensive data collection plan can crucially amplify the impact of civil society organisations and they could therefore leverage that to trace sector shifts, make concious resolutions, devise strategies for subsequent fundraising efforts, and much more.
More precisely, effective data collection can aid civil society in:
- Garnering pertinent donor data that would facilitate regular updates of donor databases and consequently make informed decisions regarding donor retention. Big Data and Artificial Intelligence also have and continue to reshape the inclusive marketing terrain, making it easy to single out key contacts, understand donor demographics and when in all probability they would support programs as well as tailoring and disseminating the targeted messaging more conveniently.
- Gauging its impact and improving on communication with the broader community which would in return help boost credibility and then be deemed a trustworthy organisation worthy of support. Storytelling is imperative in enticing fresh donors, and for that matter, data could assist in explicating the tale. On the far side of the necessity for stories, donors steadily coerce organisations for transparency. They need to understand where funds are directed and if they are utilised productively.
- Building stout, long-lasting and meaningful relationships with active supporters and those reckoned to be potential partners. Possessing unerring data, an organisation could personalise interactions, grow key engagements, and entreat support effectively. For example, in a bid to better be cognizant of the state of relationships with key audiences, an organisation could harness behavioural data, which would show how people interact with them over time. They might learn that the majority often visit their website from mobile devices and, in response, target subsequent ads to these mediums. They would also be in a position to identify which of their webpages are more popular than the rest hence, facilitate well-informed action.
- Generating adaptive decisions based on the data obtained, which would then counter crucial concerns, validate or disprove assumptions, and appraise the effectiveness of campaigns. For instance, regardless of the enormous footmark UNICEF has in the civil society space, they still carry on with gathering vast volumes of data, validating it and sharing on popular sites. After close consultation, I learnt that they harness this information to map and observe facets of human welfare such as child malnutrition, disease, sanitation, education, exploitation, and more. It is then that they measure their progress against the renown sustainable development goals and curate reports evaluating areas of attention where they could valuably allocate resources and have stakeholders enlightened.
- Boosting its financial base as data-driven organisations tend to be more financially stable which would therefore require the utilisation of metrics to direct development efforts.
Some civil society organisations are inching closer toward digital maturity albeit a fair few still playing catch-up. It therefore stands to reason that we will see more organisations prioritise data, even when confronted by the meagre of resources. This would be easy-peasy if we would get in place players like the East Africa Philanthropy Network and Candid who have audaciously embarked on an interminable expedition of leveraging data to magnify the sector’s contributions to the world and to also redefine the third sector from square one. These two excellent actors joined forces and introduced the East Africa Philanthropy Data Portal, a platform that captures data from trusts, foundations, and grant-makers operating in Kenya, Uganda, and Tanzania and looks to inform, influence decision-making and practice, and to demonstrate the impact of philanthropy on national development and the Sustainable Development Goals (SDGs).
Data in the development sector in the three states are driven by regimes that sometimes fail to regard it from or about civil society actors. Therefore, the aggregated contribution of philanthropy towards national development remains uncalculated which denies philanthropy its merited recognition and a seat at the table where crucial development conversations take place; a narrative that the data portal seeks to change. The portal collects indigenous philanthropic data while adhering to the international standards of data security, integrity, reliability and authenticity. To boot, it aims to shrink duplication of efforts and stirs up strategic cooperation between different philanthropic actors.
Have you signed up for the East Africa Philanthropy Data Portal, If not, CLICK HERE.
https://www.techtarget.com/searchdatamanagement/definition/big-data
https://www.sas.com/en_us/insights/big-data/what-is-big-data.html
https://journals.sagepub.com/doi/pdf/10.1177/2053951716631130
https://eaphilanthropynetwork.org
