The document discusses how cloud and big data management are transforming how individuals and organizations access and manage data. It notes that people now work remotely and stay connected through mobile devices, requiring ubiquitous access to data. Big data analytics can provide insights from vast amounts of structured and unstructured data to improve decision making and business processes. The document also outlines how cloud computing models like Infrastructure as a Service, Platform as a Service and Software as a Service can help organizations access scalable IT resources on a flexible, on-demand basis.

1. Cloud and Big data management: The new order
We have migrated from ‘traditional piled-file’ into an era where many individuals and organizations, from
private to government organ and non-governmental organizations require and consume huge bandwidth,
data, ubiquitous and scalable access, where people are faced with growing numbers of things to manage,
either on the go or at work. User behaviors vary with increasing social mobility. For instance, people now
work from home conveniently connecting and sharing business/official information, so they stay online at all
times through smartphones supported by 4G broadband technology, data centre, software and infrastructure
or other wireless technologies. And communication is increasingly centered around individuals and
corporate team at high speed, as people make full use of every moment to relax, learn, make decision, work,
and communicate. Fragmentation, instantaneity, and emotivity are becoming the hallmarks of everyday life.
With over 160 million people, Nigeria is Africa’s most populous country and its largest economy with nominal
GDP of $509.9 billion with service sector’s contributing 52percent while agricultural sector declined from 35
to 22percent, telecommunication 8.7percent, manufacturing with 6.8percent meanwhile oil and gas sector
declined to 14.4 from a 32.4 percent before rebasing last year, Nigeria economic potential as a large consumer
market has been in the spotlight in recent times, with economist Jim O’Neill popularizing it as one of the
“MINT” countries- alongside Mexico, Indonesia and Turkey- that he sees as successors to BRICs (Brazil,
Russia, India and China) more than a decade ago. South Africa’s 370.36 billion us dollars GDP now rank her as
continent’s second largest economy, even so Nigeria remain behind South Africa when it comes to quality
infrastructure, logistics and storage facility network, financial market development, governance,
industrialization and strong backward-integration, agricultural value chain, and structured service sector
while the aforementioned industrialization ecosystem are still largely under-served in Nigeria, making it the
most fertile ground for Information Communication Technology investment in infrastructure, platform,
application, and cloud service as an enabler of business and mitigate the loop-holes in the market.
Moving beyond big challenges
One of the growing challenges faced by a number of group operating within the Nigerian economy is
accessibility & scalability of data synchronization, reconciliation, inventory management, production flow
monitor, material supply planning, stock information analytics, customer relations management system,
management and accounting information system, delivery and logistics network.
B2B e-business; should Fuman juice team, discover the excess/abundant but rich Orange concentrate at
Teragro Farm in Markudi, negotiations and exchange can follow, even long into the future where electronic
data interchange can come in for smooth operations amidst both parties.
Big-data analytics, helps “spot variation and trend” in our swift day to day action which are pivotal to
performances auditing and development, with high level electronic data interchange EDI, storage/cloud
system, software, platform, encryption and retrievable, hardware infrastructure, which then leads into
desired lead time, market tailored offerings, precise operational segmentation, experiential learning and
insightful decision making in the boardroom.

2. Taking advantage of big possibilities
A strategic big data management, tools and processes are used to navigate the Big Data challenges so the data
management is proactive, not reactive; such are the high level critical information and data analytics towards:
 Garnering new insights
 An improved decision making
 Ease of business process re-engineering BPR for nurturing better customer experience and delivery of
service/operation
 Understand customers like never before
 Streamline operations to lower costs
 Maximize return on investment
 Provide a cost-effective scalable platform
 for exponential data growth
 Categorize and prioritize mission-critical data
 Enable the shift to open source and cloud, which help reduce working capital exposure
 Allow multi-layer encryption and drive fraud detection through predictive
 Proactive analytics
The new order for innovation, competition, and productivity
Captains in every industry will have to struggle with the implications of big data, not just a few data-oriented
managers. The increasing volume and detail of information captured by enterprises, the rise of multimedia,
social media, projectized structure and the online of Things will fuel exponential growth in data for the
foreseeable future.
Key trends
 There will be a shortage of talent necessary for organizations to take advantage of big data. Sub-
Sahara Africa has been a victim of prevailing brain drain with huge unaudited annual intellectual
flight and meanwhile the citadel of learning are not catching with the Industry, not with their near
obsolete ‘curricula and non-learning for development academic structure’ compared to the industrial
dynamism.
“ It’s well known that Africa suffers from a critical shortage of skilled professionals, mainly due to the
population’s low education level and a troubling brain drain—the steady exodus of the continent’s
highly educated workers”…Bain & Company
 Policies related to privacy, confidentiality/sensitivity of information, exemptions/clause, security,
intellectual property, and even liability will need to be set out in a big data world, because these are
crucial issues that would structure the playing field and limitations. Organizations need not only to
put the right talent and technology in place but also structure workflows and incentives to optimize
the use of big data. Access to data is critical—companies will increasingly need to integrate
information from multiple data sources, often from third parties- software service, data centre,
platform or Infrastructure, and the incentives have to be in place to enable this and big data can then
reach it full potential.

3.  There are extensive ways in which using big data can create value. First, big data can unlock
significant value by making information and record, transparent and usable at much higher rate.
Second, as organizations create and store more transactional data in digital form for future reference,
they can collect more accurate and detailed performance information on everything from supply
planning to product quality control, product inventories, to sick days of staff, and therefore exposes
variability and boost performance. Leading companies are using data collection and analysis to
conduct controlled experiments to make better management decisions; Some small and medium
business SMB are using data for basic low-frequency forecasting to high-frequency now casting to
adjust their business operations or stock level just in time like Chain Store with branches at different
location that data analytics allow to manage it stock selection, inventory, and distribution centre
along the local market shift. Third, big data allows ever-narrower segmentation of
customers/consumer and therefore much more precisely tailored products or services. Fourth,
sophisticated data analytics can substantially improve decision-making. Finally, big data can be used
to improve the development of the next generation of products and services and unearth latent
service or product. For instance, manufacturers are using data obtained from sensors or code
embedded in products to create innovative after-sales service experience such as proactive
maintenance (preventive measures that take place before a failure occurs or is even noticed).
 Those who know the market, can best serve it, big data will become a key basis of competition and
growth for individual firms. From the standpoint of competitiveness and the potential capture of
value, all companies need to take big data seriously. In most industries, established competitors and
new entrants alike will leverage data-driven strategies to innovate, compete, and capture value from
deep and up-to-real-time information. Indeed, such operation will be used going forward to unlock
sectors formally under lock and keys, most especially within the emerging Sub Sahara Africa market
that little is still known about it to Foreign Investors.
 The use of big data underpins new waves of productivity growth and industrial consumer surplus.
Big data offers considerable benefits to MSME as well as to companies and organizations. For
instance, “subscription and remote location” based services can enable the Micro Small and Medium
Enterprise Small expand and improve their operations. The Medium Enterprise Development Agency
Nigeria SMEDAN statistics shows that there are 17.7m Micro, Small and Medium Enterprises (MSME)
in Nigeria today, If a scalable modular Enterprise Resource Planning system is provided for MSME,
like chain store, Upscale bakeries, hotels, hospitals, spare‐parts dealers, auto-mechanic workshops,
clothiers/fashion shops, farmers from Animal care farm Remo to Ibiae Oil Palm field, Calabar to
Maizuba dairy farm, Minna. 17.7 million MSMEs can become the multiplier economy of our market
via data adequate arrangement and analytics, but without accurate business records, they are unable
to generate the accounting reports that financial organizations or capital venturelist can depend on
to provide financing backing to them and grow their business aggressively.
“We estimate that a retailer using big data to the full has the potential to increase its operating
margin by more than 60 percent” … McKinsey’s Global Institute (MGI)

4. Big Data
Is a broad term for any collection of data and information sets so large and complex that it becomes difficult
to process them using conventional data processing system, the challenges include analysis, capture, search,
sharing, storage, transfer, visualization, and privacy violations. The trend to larger data sets is due to the
additional information derivable from analysis of a single large set of related data, as compared to separate
smaller sets with the same total amount of data, allowing correlations to be found to "spot performance
efficiencies and market trends, prevent diseases, combat crime, distribution of national wealth, urban and
regional planning, food production and supply, fiscal policy formation, for profit and pro-bono investment
decision, geophysical characteristics of a region, manufacturing, projections, forecast and so on
Big Data Defined
Velocity – Data is streaming in at unprecedented speed and must be dealt with in a timely manner and
processed to meet the demands and the challenges which lie ahead in the path of growth and development.
Reacting quickly enough to deal with data velocity is a challenge for most organizations.
Volume – Many factors contribute to the increase in data volume. Transaction-based data stored through the
years. Unstructured data streaming from social media, previous project, sensor and machine-to-machine data,
in the past, excessive data volume was a storage issue. But with decreasing storage costs, other issues emerge,
including how to determine relevance within large data volumes and how to use analytics to create value
from relevant data. It is the size or nature of data which determines the potential and value of the data under
consideration and whether it can actually be considered as Big Data or not.
Variety – Data today comes in all types of formats. Structured, numeric, alphanumeric, coded data in
traditional databases. Information created from line-of-business applications. Unstructured text documents,
email, video, audio, stock ticker data, client history, patient’s medical record, production and financial
transactions spreadsheet, some are daily, seasonal and event data loads can be challenging to manage.
Variability – This is a factor which can be a problem for those who analyse the data or most especially
business intelligence analyst. This refers to the inconsistency which can be shown by the data at times, thus
hampering the process of being able to handle and manage the data effectively. Firms that run a seasonal or
industry with peak period like the relaxation and entertainment centres, transportation- aviation, travelling
bus operators who’s peak period remains the yuletide period.
Veracity - The quality of the data being captured can vary greatly. Accuracy of analysis depends on the
veracity of the source data.
Complexity – High volume Data analytics is a complex process, especially when large volumes of data come
from multiple sources. So there is a pivot need to match, cleanse and transform data across platforms.
However, it is necessary to connect and correlate relationships, hierarchies and multiple data linkages in
order to decode the information adequately

5. Major enabler
Big data has increased the demand of information management, solution architecture, technology
infrastructure and software specialists like Huwaei, Ericsson, Alcatel, Motorola, Software AG, Oracle
Corporation, IBM, Dell, Microsoft, SAP, EMC, HP ,CWG, Resourcery, Sigma Alliance and have invested more in
software and infrastructure for data management and analytics.
Cloud computing
It all about sharing of resources to achieve coherence and economies of scale, similar to a utility (like the
electricity network) over a grid. At the foundation of cloud computing is the broader concept of converged
infrastructure and shared services. I.e. Information Technology utility enabler (provider) - enabling (client)
on a service or subscription based business structured. An ICT methodology that helps eliminate all the
proprietary cost, infrastructure capital, software, platform and re-current expenditure of an organization
Information Technology need while create room for expertise or specialization, scalability and advancement
at every level.
The term "moving to cloud" also refers to an organization moving away from a traditional CAPEX-capital
expenditure model (buy the dedicated hardware and depreciate it over a period of time) to the OPEX-
operational expenditure model (use a shared cloud infrastructure and pay as one uses it).
Service models
Cloud computing providers offer their services according to several fundamental models:
 Infrastructure as a service (IaaS)
In IaaS model, cloud providers deliver all the hardware infrastructure and support like the virtual
machines, load balancer, server, storage device to data centre, power and power back-up,
monitoring.
 Platform as a service (PaaS)
In the PaaS models, cloud providers deliver a computing platform, typically including operating
system, programming language execution environment, database, and web server.
 Software as a service (SaaS)
In SaaS model, cloud provider delivers accessible application software and database. Such a cloud
provider manages the infrastructure and platforms that run the applications. SaaS is sometimes
referred to as "on-demand software" and is usually priced on a pay-per-use basis. I.e. subscription
based business.
 Unified Communications as a Service (UCaaS)
In UCaaS model, cloud provider delivers multi-platform high definition audio-visual communications
over the network which is designed, deployed and run by the service provider real time-real life. The
services could be in different devices, such as purposed designed wide screen, computers and mobile
devices. Services may include IP telephony, unified messaging, video conferencing and mobile
extension.