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How To Get Data Right

Organizations continue to capture huge volumes of data from different sources — be it from internal silos, data at rest, live data or other sources, to monitor and understand market movers, ultimately to improve operational efficiencies and customer service. Various market research reports indicate that organizations are spending considerable amount of money, time and effort on data analytics, to gain a competitive edge against competition; but, for many, all of these has only been somewhat effective in meeting the primary objective of their data. There is still a large percentage of organizations that have not started seeing any major benefits. The questions of “Are we getting the best value for everything we buy?” often goes unanswered, because data unification processes and approaches aren’t taken very seriously.

Let’s take a look at what organizations’ focus should be

One of the biggest challenges that organizations face today, is the approach to data integration from various systems.

This has only intensified over time, as the volume and variety of usable data has only increased exponentially, and as a result, trying to meet today’s data integration demands with yesterday’s data integration approaches is impractical because of scalability and architectural limitation.

Bahwan Cybertek’s (BCT) business partnership with TIBCO in recent times is to bring in the world class Integration, API management and Analytics to the business users coupled with industry focused software tools developed inhouse by BCT is to take digital transformation to its holistic approach.

Organizations have to see analytics as an everyday tool: one that acts as an enabler for informed decision-making, with continuous improvements based on feedback from respective stakeholders. It should not be forgotten that it’s the business owners who are the best people to suggest what data should be analyzed; they should be part of the data strategy from day one. Any data strategy driven from a technology perspective alone is bound to fail.

The analytics practice should not be viewed as a technology driven project that which pumps information by crunching data from various silos and streams, for business owners to take decisions upon. Without the business understanding of what needs to be achieved, one will never know what type of data needs to be analyzed, and how. The true value of any information can only be appreciated by business owners who can understand the data results, and understand how they can be applied to improve business problems.

As I said earlier, incorporating data analytics as a core business process in an organization should be business driven, while its purpose has to be clearly defined in a blueprint for immediate action and continuous enhancements — the selection of required analytics tools should be based on this principal. Often, traditional machine learning algorithms are sufficient to analyze data, instead of products that support complex algorithms, unless there is an absolute necessity for such technology. A thoughtful selection will avoid the waste of time and money in building complex models, when simpler approaches would easily meet the business need. Operationalization always takes precedence over model sophistication — the adage the saying “don’t let the perfect be the enemy of the good” is apt for organizations looking to quickly transform data into action.

Bahwan Cybertek’s IP based software RETINA for predictive analytics, and ASYMMETRIX for risk management (built with machine learning capabilities) are built to support business users to be able to take timely informed decisions.

It’s very important to remember that in analytics there cannot be a failure when business provides continuous feedback, and the process is designed in such a way that the system is capable to capture the feedback and make constant changes to the model. It should be noted that analytics is not a project that starts and ends, but rather an ongoing organizational process that serves a number of business objectives over time.

Companies become successful when the focus on data analytics is made a culture within the organization; this will transforms raw data into actions on a continuous basis, directly impacting customer service, process efficiencies, competitive advantage, et cetera.

By delivering a process that starts and ends with the business, data analytics should ensure that machine learning efforts don’t end up locked in a black box and isolated with no impact on business behavior and outcomes. Data analytics demands an approach that engages both IT and business stakeholders, and focuses on tangible outcomes and continuous improvement.

Digitally empowered businesses have the greatest potential to be successful in the current technology-driven economy. At BCT, our team of UX and UI designers and developers combine user psychology, design experience and technology expertise, to support customers, create and engage consistent digital experiences across channels, providing new opportunities for accelerated growth.

Given the complexity of data aggregation and data correlation, and the use of statistical tools & machine learning for automation, many organizations today hire outsiders to provide the required services. They try to automate input data sets into output without human intervention; one obvious consequence of this approach is that if you hire an outside service, you are more likely to rehire them for each additional task, offering the consultants a guided tour through your wallet over time. Additionally, a fully automated operation is unlikely to be successful in any enterprise, as there will always be a requirement for human guidance to ensure data quality and reliability. System development should always be able to ask the human expert for input when it is unsure of the answer. In my opinion, organization will be better off developing in-house teams, initially to work with external vendors to gain experience and competence over time, and later provide the required services in-house.

Getting it all right is very challenging, and only a handful of companies worldwide have been able to see the real value of data by embedding analytics into every function of their organization. To be successful, companies should focus on the following:

At Bahwan CyberTek, we work with functional teams to gather, analyze and define business requirements to understand user goals. Our solutions are based on extensive research of target market, competitors and market conditions. This approach guarantees fit for purpose solution that is closely aligned with your business and the psychology of your target audience.

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