Enterprises and cloud computing become more integrated and
essential for gain or maintain a competitive advantage through big data and
Analytics. Cloud is now essential in improving operations efficiency and
synergy. To optimize the enterprise architecture with the cloud, there are a
few strategic questions need to be considered;
how much cloud business does your enterprise need?
what cloud strategy best meets your enterprise operational and security needs?
do private, public clouds, or hybrid cloud fit in your enterprise’s information
workload deployment strategy?
fit in the enterprise’s information workload deployment strategy?
is A Multi-cloud Strategy?
This probably is the point where the narrative should
introduce the principle of multi-cloud. A multi-cloud is an approach to cloud
computing which seeks to optimize enterprise costs, Return-On-Investment (ROI),
and enabling big data analytics, which is already evolving the information
workload deployment strategy of many organizations. Multi-cloud has already
affected the major software and Software-As-A-Service (SaaS) providers, which
have been rapidly evolving their application suites to enable this new
reality. As recently as this week, IBM
announced that they had moved its Cloud-native software architecture.
Time To Consider A Multi-Cloud Strategy For Your Enterprise?
Multi-cloud is a cloud computing strategy seeks to align from
different cloud providers capability to optimize different business operations
and technical requirements. A multi-cloud strategy can be a way to reduce the
dependence upon more traditional software vendors and or on a single cloud
Of A Multi-Cloud Strategy
The advantages of a multi-cloud enterprise information
workload deployment strategy are:
enterprise can still operate even if one or more of the clouds providers goes
offline or encounter other difficulties.
can avoid vendor lock-in since the enterprise’s data is stored on different clouds
service providers and could be migrated if need be.
can provide a reduction in the scales of data breach vulnerability since
breaching one cloud does not provide access to the entire data of your
enterprise, even if your organization has not implemented hybrid-cloud
(private/public) strategy because all the data simply isn’t all housed one cloud.
multi-cloud solutions are customizable. Every enterprise can select what works
best in order to achieve optimal efficiency.
Of The Multi-Cloud
The multi-cloud enterprise information workload deployment
strategy has downsides as well. For instance:
across the multi-cloud providers may require more planning, relationship
management, and strategic oversight.
implementations, while reducing the potential scale of any one security breach,
it does provide more than one potential breach point to be monitored, managed,
Based on your enterprise’s industry, use of big data technologies, information security needs and the use information analytics to gain or maintain a competitive advantage and or comparative advantage, a multi-cloud enterprise information workload deployment strategy has a place in optimizing your enterprises technical and information strategy. Especially when your multi-cloud strategy includes a hybrid-cloud (public/private) as a major pillar in your cloud strategy.
data-driven decision making is at the center of all things. The emergence of
data science and machine learning has further reinforced the importance of data
as the most critical commodity in today’s world. From FAAMG (the biggest five
tech companies: Facebook, Amazon, Apple, Microsoft, and Google) to governments
and non-profits, everyone is busy leveraging the power of data to achieve final
goals. Unfortunately, this growing demand for data has exposed the inefficiency
of the current systems to support the ever-growing data needs. This
inefficiency is what led to the evolution of what we today know as Logical Data
What Is a Logical
simple words, a data lake is a data repository that is capable of storing any
data in its original format. As opposed to traditional data sources that
use the ETL (Extract, Transform, and Load) strategy, data lakes work on the ELT
(Extract, Load, and Transform) strategy. This means data does not have to be
first transformed and then loaded, which essentially translates into reduced
time and efforts. Logical data lakes have captured the attention of
millions as they do away with the need to integrate data from different data
repositories. Thus, with this open access to data, companies can now begin to
draw correlations between separate data entities and use this exercise to their
Primary Use Case
Scenarios of Data Lakes
Logical data lakes are a
relatively new concept, and thus, readers can benefit from some knowledge of
how logical data lakes can be used in real-life scenarios.
Experimental Analysis of Data:
Logical data lakes can
play an essential role in the experimental analysis of data to establish its
value. Since data lakes work on the ELT strategy, they grant deftness and speed
to processes during such experiments.
To store and
analyze IoT Data:
Logical data lakes can
efficiently store the Internet of Things type of data. Data lakes are capable
of storing both relational as well as non-relational data. Under logical data
lakes, it is not mandatory to define the structure or schema of the data
stored. Moreover, logical data lakes can run analytics on IoT data and come up
with ways to enhance quality and reduce operational cost.
To improve Customer
Logical data lakes can
methodically combine CRM data with social media analytics to give businesses an
understanding of customer behavior as well as customer churn and its various
To create a Data
Logical data lakes
contain raw data. Data warehouses, on the other hand, store structured and
filtered data. Creating a data lake is the first step in the process of data
warehouse creation. A data lake may also be used to augment a data warehouse.
reporting and analytical function:
Data lakes can also be
used to support the reporting and analytical function in organizations. By
storing maximum data in a single repository, logical data lakes make it easier
to analyze all data to come up with relevant and valuable findings.
A logical data lake is a comparatively new area of study. However, it can be said with certainty that logical data lakes will revolutionize the traditional data theories.
The 360-degree view of
the consumer is a well-explored concept, but it is not adequate in the digital
age. Every firm, whether it is Google or Amazon, is deploying tools to
understand customers in a bid to serve them better. A 360-degree view demanded
that a company consults its internal data to segment customers and create
marketing strategies. It has become imperative for companies to look outside
their channels, to platforms like social media and reviews to gain insight into
the motivations of their customers. The 720-degree view of the customer is
further discussed below.
What is the
720-degree view of the customer?
A 720-degree view of the customer refers to a
three-dimensional understanding of customers, based on deep analytics. It
includes information on every customer’s level of influence, buying behavior,
needs, and patterns. A 720-degree view will enable retailers to offer relevant
products and experiences and to predict future behavior. If done right, this
concept should assist retailers leverage on emerging technologies, mobile
commerce, social media, and cloud-based services, and analytics to sustain
lifelong customer relationships
What Does a
720-Degree View of the Customer Entail?
Every business desires to cut costs, gain an
edge over its competitors, and grow their customer base. So how exactly will a
720-degree view of the customer help a firm advance its cause?
Social media channels help retailers interact
more effectively and deeply with their customers. It offers reliable insights
into what customers would appreciate in products, services, and marketing
campaigns. Retailers can not only evaluate feedback, but they can also deliver
real-time customer service. A business that integrates its services with social
media will be able to assess customer behavior through tools like dislikes and
likes. Some platforms also enable customers to buy products directly.
Customer analytics will construct more detailed customer profiles by
integrating different data sources like demographics, transactional data, and
location. When this internal data is added to information from external
channels like social media, the result is a comprehensive view of the customer’s
needs and wants. A firm will subsequently implement more-informed decisions on
inventory, supply chain management, pricing, marketing, customer segmentation,
and marketing. Analytics further come in handy when monitoring transactions,
personalized services, waiting times, website performance.
The modern customer demands convenience and
device compatibility. Mobile commerce also accounts for a significant amount of
retail sales, and retailers can explore multi-channel shopping experiences. By
leveraging a 720-degree view of every customer, firms can provide consumers
with the personalized experiences and flexibility they want. Marketing
campaigns will also be very targeted as they will be based on the transactional
behaviors of customers. Mobile commerce can take the form of mobile
applications for secure payment systems, targeted messaging, and push
notifications to inform consumers of special offers. The goal should be to
provide differentiated shopper analytics.
Cloud-based solutions provide real-time data across multiple channels, which illustrates an enhanced of the customer. Real-time analytics influence decision-making in retail and they also harmonize the physical and retail digital environments. The management will be empowered to detect sales trends as transactions take place.
The Importance of
the 720-Degree Customer View
Traditional marketers were all about marketing
to groups of similar individuals, which is often termed as segmentation. This technique
is, however, giving way to the more effective concept of personalized
marketing. Marketing is currently channeled through a host of platforms,
including social media, affiliate marketing, pay-per-click, and mobile. The
modern marketer has to integrate the information from all these sources and
match them to a real name and address. Companies can no longer depend on a
fragmented view of the customer, as there has to be an emphasis on
personalization. A 720-degree customer view can offer benefits like:
Firms can improve customer acquisition by
depending on the segment differences revealed from a new database of customer
intelligence. Consumer analytics will expose any opportunities to be taken
advantage of while external data sources will reveal competitor tactics. There
are always segment opportunities in any market, which are best revealed by
real-time consumer data.
Marketers who rely on enhanced digital data can
contribute to cost management in a firm. It takes less investment to serve
loyal and satisfied consumers because a firm is directing addressing their
needs. Technology can be used to set customized pricing goals and to segment
New Products and
Real-time data, in addition to third-party information, have a crucial impact on pricing. Only firms with a robust and relevant competitor and customer analytics and data can take advantage of this importance. Marketers with a 720-degree view of the consumer across many channels will be able to utilize opportunities for new products and personalized pricing to support business growth
The first 360 degrees include an enterprise-wide
and timely view of all consumer interactions with the firm. The other 360
degrees consists of the customer’s relevant online interactions, which
supplements the internal data a company holds. The modern customer is making
their buying decisions online, and it is where purchasing decisions are
influenced. Can you predict a surge in demand before your competitors? A
720-degree view will help you anticipate trends while monitoring the current
View and Big Data
Firms are always trying to make decision making
as accurate as possible, and this is being made more accessible by Big Data and
analytics. To deliver customer-centric experiences, businesses require a
720-degree view of every customer collected with the help of in-depth analysis.
Big Data analytical capabilities enable monitoring
of after-sales service-associated processes and the effective management of
technology for customer satisfaction. A firm invested in being in front of the
curve should maintain relevant databases of external and internal data with
global smart meters. Designing specific products to various segments is made
easier with the use of Big Data analytics. The analytics will also improve
asset utilization and fault prediction. Big Data helps a company maintain a
clearly-defined roadmap for growth
It is the dream of every enterprise to tap into
customer behavior and create a rich profile for each customer. The importance
of personalized customer experiences cannot be understated in the digital era.
The objective remains to develop products that can be advertised and delivered
to customers who want them, via their preferred platforms, and at a lower
During the software engineering process, there are different issues which should be dealt with or else they will subject the project to unnecessary costs later. The technical debt perspective should be considered in each step of software development. For instance, when analyzing the cost of cloud approaches, you need to take into consideration the technical debt. You should as well factor the engineering aspect when making technical decisions such as choosing between cloud services vs. homegrown solutions.
What is technical debt?
Technical debt refers to the implied cost which will be incurred to do additional rework on a system after the engineering process is done. For example, engineers can choose to go for an easy option so that they can save time during the product design. The right steps which they will avoid will later need to be implemented which will mean a product has to be recalled or it will have to be fixed after it has reached the market which will cost more in terms of resources and manpower.
What are the most common types/causes technical debts?
Deliberate tech debt
In this case, engineers are aware of the step which is necessary during project implementation, but they will ignore it provided they can go for a shortcut which will save on cost and avail the product to the market. For instance, when analyzing the advantage of using the public cloud, some engineers may assume certain benefits, and later they will realize they are very necessary hence they are forced to go back and procure the system. It will lead to wastage in the company. Some engineers will not like doing the same process every now and then; they can avoid a given process only to expose the final product to flaws which will require re-engineering.
Accidental/outdated design tech debt
After designing a product or software, with time the technology will advance and render the design less effective in solving certain needs. For instance, due to advancement in technology, the tools you incorporated in a given software may end up being flawed which will make the product less effective which may necessitate re-engineering. Engineers may try their level best to come up with great designs, but advancement in technology can make their designs less effective.
Bit rot tech debt
It is a situation where a complexity develops over time. For example, a system or a component can develop unnecessary complexity due to different changes which have been incorporated over time. As engineers try to solve emerging needs, they can end up exposing the product to more complications which can be costly in the long run.
Strategies for minimizing technical debt
How to minimize deliberate tech debt
To avoid the tech debt, you need to track the backlog when engineers started the work. If you can track the backlog and identify areas where the engineers are trying to save time, you can avoid the debt.
Minimizing Accidental/outdated design tech debt
You need to refactor the subsystem every now and then so that you can identify the technical debt and fix it. For example, if the software is exposing you to unnecessary slowdowns, you need to fix the errors and make it meet industry standards.
Addressing Bit rot tech debt
Engineers should take time to understand the system they are running and clear any bad codes.
A public cloud strategy refers to a situation where you utilize cloud resources on a shared platform. Examples of shared or public cloud solutions include Microsoft Azure, Amazon Web Services and Google cloud. There are several benefits associated with cloud solutions. On the other hand, a private cloud strategy refers to a situation where you can decide to have an infrastructure which is dedicated to serving your business. It is sometimes referred to as homegrown where you employ experts to run the services so that your business can access different features. There are several advantages of using a public cloud over private cloud which you should know before you make an informed decision on the right platform to invest. Some of the benefits of the public cloud strategy include the following:
Availability and scale of Expertise
If you compare the public cloud and the private cloud services, the public cloud
allows you to access more experts. Remember the companies which offer the cloud services have enough employees who are ready to help several clients. In most cases, the other clients whom the service providers serve will not experience problems at the same time. It implies that human resource will be directed toward solving your urgent issue. You can as well scale up or down at any given time as the need arises which is unlike a case of private cloud solutions where you will have to invest in infrastructure each time you will like to upgrade.
Downgrading on a private cloud system can expose you to lose because you will leave some resources underutilized.
The volume of Technical Resources to apply
You access more technical resources in a public cloud platform. Remember the companies which offer the public cloud solutions are fully equipped with highly experienced experts. They also have the necessary tools and resources which
they can apply to assure you the best technical solutions each time you need them. It is unlike a private arrangement where you will have to incur more costs if the technical challenges will need advanced tools and highly qualified experts.
The price of a private cloud is high when compared to a public arrangement. If you are looking for ways you can save money, then the best way to go about it is to involve a public cloud solution. In the shared platform, you will only pay for
what you need. If you do not need a lot of resources at a given time, you can downgrade the services and enjoy fair prices. Services such as AWS offer great cost containment across the time which makes it easy to access the services at fair prices. For any business to grow, it should invest in the right package which brings the return on investment. The services offered by the public cloud systems allow businesses to save and grow. You should as well take into consideration other factors such as ecosystems for cloud relationships before you make an informed decision. There are some business models which prefer private cloud solutions while others can work well under public cloud-based solutions.
Unix and Linux are different operating systems with have some common commands. Source code for Linux is freely available to the public and Unix is not available. Linux operating system is a free/open source and Some versions of Unix are proprietary and others are a free/open source. Linux Operating system can be used for desktop systems and for servers. But the Unix is mainly used in servers, mainframes and high-end computers.
AIX is an operating system based on Unix versions from IBM. It is mainly designed for IBM’s workstations and for the server hardware platforms. And HP-UX is the operating system from HP ( Hewlett Packard ) based on Unix versions. HP-UX and AIX are stable operating system compare with Linux. HP-UX and AIX are platform dependent and they are limited to their own hardware. But in the case of Linux, it is platform independent and can be used with any hardware. Since HP-UX and AIX are platform dependent, they are optimised for the hardware and the performance is better than Linux operating systems. AIX is outperforming Linux from 5 to 10 percent.
AT&T Unix, started in the 1970s at the Bell Labs and newer versions of Unix have developed and some of them are listed below. In 1980, AT&T licensed Unix to third-party vendors and leading to the development of different variants. Some of them are;
Berkeley Unix, FreeBSD and its variants
Solaris from Sun Microsystem
HP-UX from Hewlett-Packard
AIX from IBM
MacOs from Apple
Unix installations are costlier since it requires some special hardware. MacOS needs apple computers, AIX needs IBM hardware and HP-UX needs HP hardware etc.
Linux is a free and open source operating system based on Unix. Linux kernel was first developed by Linus Torvalds in 1991. Linux was originally developed for personal computers but nowadays it is using personal computers as well as in server systems. Since it is very flexible, it can be installed in any hardware systems. Linux operating system is available for mobile phones, tablets, video game consoles, mainframes and supercomputers. Some of the best distros for small business are;
Linux Vs Unix
The Source Code of Linux is freely available to its Users.
The Source Code of Unix is not available for the general public.
Linux primarily uses Graphical User Interface with an optional Command Line Interface.
Unix primarily uses Command Line Interface.
Linux OS is portable and can be executed in different Hard Drives.
Unix is not portable.
Linux is very flexible and can be installed on most of the Home Based Pcs.
Unix has a rigid requirement of the Hardware. Hence, cannot be installed on every other machine.
Linux is mainly used in Home Based PC, Mobile Phones, Desktops, etc.
Unix is mainly used in Server Systems, Mainframes and High-End Computers.
Different Versions of Linux are: Ubuntu, Debian, OpenSuse, Redhat, Solaris, etc.
Different Versions of Unix are: AIS, HP-UX, BSD, Iris, etc.
Linux Installation is economical and doesn’t require much specific and high-end hardware.
Unix Installation is comparatively costlier as it requires more specific hardware circuitry.
The Filesystems supported by Linux are as follows: xfs, ramfs, nfs, vfat, cramfsm ext3, ext4, ext2, ext1, ufs, autofs, devpts, ntfs
The Filesystems supported by Unix are as follows: zfs, js, hfx, gps, xfs, vxfs.
Linux is developed by an active Linux Community worldwide.
Unix is developed by AT&T Developers.
Most commercial versions of UNIX distributions are coded for specific hardware. Like HP-UX for PA-RISC (Hewlett-Packard) and Itanium machines (Intel) and AIX is for Power processors ( IBM ). Since these distributions are limited, the developers can optimise their code for these architectures to get maximum utilisation of resources. Since it uses proprietary hardware, Unix distributions are not cost effective.
HP-UX needs HP or Intel hardware
AIX needs IBM Hardware
Linux operating system is not dependent on the hardware, so it can be installed in any of the server systems which have a processor. Since the developers cannot assume the hardware architecture and they need to prepare the code for some general hardware specifications and that’s why Linux operating system has less performance than the commercial Unix variants.
Linux is open to all hardware
GNU General Public License (GPL), is a form of copyleft and is used for the Linux kernel and many of the components from the GNU Project. Free software projects, although developed through collaboration, are often produced independently of each other. AIX and HP-UX are using proprietary licenses.
Unix (System V)
1982; 36 years ago
Monolithic with dynamically loadable modules
1986; 32 years ago
Monolithic with dynamically loadable modules
Community, Linus Torvalds
Primarily C and assembly
September 17, 1991; 26 years ago
Monolithic (Linux kernel)
GPLv2 and other free and open-source licenses (the name “Linux” is a trademark[b])
Softwares and Tools
Softwares and tools in Linux are general to all hardware. But in the case of Unix, separate tools and software which leverage to get the maximum performance. So the performance of the systems is higher than the Linux operating system by comparing the hardware configuration. Unix has good performance than Linux systems. While considering the cost estimation, Linux will get more votes.
System Management Interface Tool ( SMIT ) with AIX is the tools used for package management, System Administration Manager (SAM) on HP-UX. Linux operating system uses rpm or dpkg etc. based on the variants.
Software Installation and Patch Management
R H Linux
rpm -i file
swinstall –s depot software
installp –a [-c] FileSet
rpm -U/F file
swinstall –s depot software
installp –a FileSet
swlist –l product
lslpp –L all
installp –u FileSet
rpm -q -a
swlist –l product
lslpp –L all
While talking about the file systems, Linux scores more than the other Unix versions. Unix supports two or three file systems locally. But Linux supports almost all the file systems available on any operating system.
The kernel is the core of the operating system and the source code of the kernel are not freely available for the commercial versions of Unix. For the Linux operating system, the users can check and verify the code and even modify it if required.
The commercial versions of Unix come with a license cost. Since these operating systems are purchased, the vendor will provide technical support to the end users to the smooth running of the operating systems.
In the case of the Linux operating system, we need to use the open source forums and community for getting support from the users and developers around the world or hire some freelancers for fixing the issues.