Archive for the ‘Business Intelligence’ Category
During the annual Health Information and Management Systems Society conference, IBM CEO Ginni Rometty declared that the era of cognitive computing in healthcare is upon us.
“It actually is an era that will play out in front of us, which is what we call the cognitive era,” Rometty said. “I hope to persuade you … that this idea of cognitive healthcare, systems that learn, that this is real and it’s mainstream and it is here and it can change almost everything about healthcare.”
The official IBM website says that IBM Watson Healthcare mission is to empower leaders, advocates and influencers in health through support that helps them achieve remarkable outcomes, accelerate discovery, make essential connections and gain confidence on their path to solving the world’s biggest health challenges.
Let’s look into what IBM Watson is and what exactly it will bring us.
IBM Watson is an advanced artificial intelligence program that is transforming healthcare into a quantifiable service where every bit of information is available and physicians only have to go through their personalized reports instead of reading through dozens of papers for every patient’s case.
Here are just some upgrades that IBM Watson will bring to healthcare.
Your doctor will be well-informed
At the moment one of the most significant challenges in healthcare is the huge amount of information available. Your doctor can not be aware of all the information that has been published recently. Watson however is able to search all the information, so doctors don’t have to spend hours and hours on reading and investigating.
It’s currently being used in genome analysis research at a hospital in the US where it found a third of patients were affected by information published in articles since their treatments began.
You’ll be recommended better treatments
If, for example, you’re diagnosed with cancer, you might benefit from the platform, Watson for Oncology. Usually the doctor meets with cancer patients and spends time reviewing their notes – which would be presented in paper format or in a list of emails. It turns out that A doctor’s decision will be made basing on his individual experience and the information available in front of him.
IBM Watson takes all those unstructured notes and restructures it in a way that the doctor can check easily, with treatment recommendations of which drug to give, which radiation or dosage.
You will be prescribed better medication
A very important aspect of IBM Watson is medication. Generally it takes about 12 years to produce a pill, but recent tests at the Baylor College of medicine in Houston, Texas, has reduced significant parts of the research process to weeks, months, and days. IBM Watson is able to accelerate the discovery of new treatment by streamlining research processes. As a patient, you will benefit from having more appropriate treatments available for you when you need it.
It’s clear that IBM Watson is already transforming healthcare, but much progress still lies ahead.
“We’re just at the beginning of something that will be very big and very transformative over the next 50 years,” said Watson Healthcare Executive Lead, Thomas Balkizas.
Feel free to share your thoughts about IBM Watson prospects for the near future in comments below!
Business Development Manager
Professional Software Development
Digital health is dramatically reshaping and redefining how healthcare is delivered. And here are some new trends that we can observe now and which are expected to change the future of eHealth.
New technological aids has changed the relationship between patient and doctor. Patients can now google information about illnesses and treatments, read their digital patient journal online, learn of their doctor’s findings and take responsibility for their own care in a completely different way than in the past.
The use of digital and mobile IT solutions in healthcare means that care is no longer available only in a specific location. Nowadays, patients have the right to choose where they wish to be treated and, in the future, this will not only include choosing which hospital to visit, but also whether to hold their appointments via video link or to treat their depression using online therapy.
Apps and mobile technology are already a natural part of our everyday life.
There is a number of eHealth applications now available and one of them is the digital diary which allows patients to record measurement data and appraisals or to note down their general physical and mental states during the day. As a next step they forward this information to their doctor.
Apps like this also give patients a simple means by which to take greater control over their own well-being, whether related to blood-sugar levels, blood pressure, or mood.
At the moment, healthcare do not use all the rich data that this type of smart device can provide. However, through projects such as the Swedish eHealth Agency’s Health for Me and other platforms that allow patients to collect their health data, an attempt is being made to both understand and find ways to utilize this digital “treasure” for the benefit of both patients and providers.
One major feature of eHealth is large IT systems. These are designed to suit a broad user base, however, which invariably makes it difficult for them to cater specifically to any one user. The future lies in creating smaller, customized systems that can communicate with one another through their interoperability. Custom-designed digital solutions entail opening up the market to small-scale actors and utilizing the entire ecosystem during development.
Big Data has changed the way we manage, analyze and operate data in any industry. Healthcare is obviously one of the most promising areas where Big Data can be applied to make a change. In future perspective healthcare analytics can reduce costs of treatment, predict outbreaks of epidemics, avoid preventable diseases and improve the quality of life in general. Treatment delivery methods face new challenges today: average human lifespan is increasing together with the world population. Healthcare professionals, just like business entrepreneurs, are capable of collecting massive amounts of data and look for best strategies to use these numbers.
Even if healthcare services is not something that exсites you, still you are a potential patient, and just like everyone of us you should be aware about new healthcare analytics applications and how they can help you.
Anytime a new technology enters healthcare, there are a number of challenges it faces. Common setbacks of artificial intelligence in healthcare include a lack of data exchange, regulatory compliance requirements and patient and provider adoption. AI has come across all of these issues, narrowing down the areas in which it can succeed.
The most popular use of artificial intelligence in healthcare is in IBM’s smart cloud, where Watson lives. The Watson platform has been used in a number of disciplines within healthcare including with payers, oncology and patient risk assessment.
To know more about the way IBM Watson works and its perspectives for the future please check out my new article “IBM Watson. Future is closer than you think” next week.
Business Development Manager
Professional Software Development
When a technical term is used more and more frequently the exact definition becomes “blurred” and its true meaning is usually greatly distorted.
This what happened to the term ‘business intelligence’ or BI. Ever since, when the term had only appeared, the development of technologies has substantially expanded our understanding of BI and of what advantage and benefit the company can retrieve from their available data.
So, what does ‘business intelligence’ mean today? How it could be useful for companies and how to apply its underlying ideas correctly to ensure the steady growth of efficiency and profitability of a business?
What is business intelligence? Why is it important?
BI consists of two completely diverse, but at the same time complementing one another aspects.
- Value for the business.
Implies how companies can use the available information in order to multiply profit and efficiency and bring new products and services to the market successfully.
- IT strategy.
Includes the idea of what technological solutions to apply in order to achieve greatest possible utility of BI.
Presentation of data in a specific format for efficient usage by the company has always been a challenging task. For many organizations, it is quite complex to determine what particular information is required for a specific use.
Such business analysis requires certainty in methodologies and goals.
Earlier BI resources were limited by the lack of available data collection technologies. Nevertheless, modern technologies such as big data, analytics, mobile services and cloud computing in their combination allow obtaining a continuous flow of detailed information quite fast and with no serious investments.
Still, the current bottom line lies in extracting some valuable sense from these data and, in many respects, it is much more complicated than collecting information itself.
Five efficiency criteria of BI-system (and BI-strategy)
1. While selecting a BI-system one should be guided by the real needs of a particular company
The most common and at the same time the most dangerous mistake is when the BI-systems dictate the strategy of their usage. As a result, the company gets plenty of non-synchronized applications, awkward interface and the infrastructure that is already out of date, yet so entrenched in the IT system that could be barely substituted.
2. Be flexible
Flexible model of the integration of the appropriate software involves constant repetition of certain operations with the gradual development of the system. This allows companies to evaluate the success of the project at any point of time, to determine at what stage it is and towards what it moves.
As a rule, creating, testing and integration of BI-technologies goes much more smoothly when the company receives real-time feedbacks from all the running processes and is able to make required adjustments on the fly. It is vital for BI-systems!
3. User-friendly interface
BI-solutions focus on collection, visualization and management of the data.
Usually, when it comes to large amounts of numeric information companies face a risk to get exceptionally technical, inconvenient and incomprehensible data for the “illiterate” users of the system. This information is highly functional, but impractical, especially when it is badly integrated with other applications.
Integration is a key point in deploying BI-technologies. In case the interface is non-intuitive, complex and inconvenient for the end users, BI-system will definitely work inefficiently.
There is a tendency to allocate significant resources for the integration of the latest technologies promising unprecedented results. However, such investments potentially may do more harm than good. Intelligent, targeted and smooth integration is the key to avoid serious errors during implementation.
4. BI is a tool available to everyone
BI has been long used by completely different users, not only by experts with appropriate education and experience. BI-system should be simple and easy to understand to everyone.
For this purpose, companies have to attain the convenience of analytics and the reports drawn on its basis; it should be simple and demonstrative. The collected data should be presented in the way so that any user could easily make definite conclusions.
5. Centralize your data
The desire to achieve the result, based on useful information implies proper data handling. Receiving data from multiple sources and storing it in a centralized information DB, capable of filtering, sorting and removing the unnecessary is critical for the deployment of the applications involved into making business decisions. Apart from that, risk management also becomes more effective through transparency and structure.
General excitement over BI is evident
The role that IT plays in the world has significantly changed over the past few years thanks to the information ‘boom’. Still, construction of a technological infrastructure is not enough for successful data management.
That is why, ‘business intelligence’ it is not just a fashionable term it is a concept that demonstrates the need to move beyond the paradigm of a separate, isolated existence of data analysis and business goals.
In fact, BI reminds us that technologies and business must be closely linked, so that the business goals and business guidelines predetermine the choice of software and, the software in return would provide useful information leading business to success.
Business Development Manager
Professional Software Development
I guess you have already read/heard a lot about CRM and BI, so in this article you will not find description what BI and CRM is. Also you will not find such dispute as “CRM vs BI” or “Why BI is not CRM” etc. What, then, is to discuss? 🙂
Let’s imagine BI and CRM in its tandem.
The discipline of business intelligence includes a broad range of functional activities from data mining and statistical analysis to predictive modeling and reporting. So, BI-applications are often positioned as an indispensable tool for decision making at the tactical and strategic levels. As a rule in this case to work with information efficiently we will need enterprise data warehouse, building of which could “seed” at least half of the total budget for BI, in addition analytical models are rather expensive. Under these circumstances, the need of significant investment is one of the most essential and restrictive factors of dissemination of Business Intelligence systems. At the same time, experience shows that the usage of BI-applications can be fully justified at the operational level, where decisions must be taken exactly in real time. In this approach, building corporate Data Warehouse is not critical, and the using of pre-configured models is not necessary, because BI allows to implement arbitrary “point” data depending on the situation. If you don’t mind I would like to illustrate it with a concrete example.
Let’s consider a small example. For CRM-system we will take Oracle Siebel CRM, as for BI-application it will be Oracle BI. To implement CRM for realizing sms-mailing was proposed to use a single sms-gateway. Let’s assume that the frequency of such mailing is quite high, and volume is measured in ten of thousand of sms. Taking into account that the sms-gateway is just a tool of message transfering, you need to monitor constantly the process of mailing considering the timeline plan, “black lists”, the spam load per user, etc. In this case, in spite of the high performance of Oracle Siebel CRM,it is unreasonable to exchange data between the CRM-system and sms-gateway in online, but it`s reasonable to use additional transit system, which would redistribute the load. When you run a marketing campaign such a system would import data from Oracle Siebel CRM and after the campaign would pass results to the CRM-system . But, at the same time, in case any error arise or a failure campaign reaction time for the problem is reduced, you will know this only after the campaign ends and it may adversely affect the relationship with the client. You could solve this problem either using an expensive integration or through the using of BI-application. For example, Oracle BI enables to control the process of distribution and evaluate the results based on the data from the three systems online. Thus, in case of a large number of notifications incoming to the sms-gateway, that a message is not delivered to the recipient, it would be possible to stop the campaign quickly and make changes promptly, rather than waiting for its completion. Furthermore, using BI in this situation allows to correct the results during the campaign.
So the best effect in the marketing process could be obtained from using BI-applications at the operating level. Also effective BI-applications could be demonstrated in other CRM-processes. In sales BI-applications are indispensable in launching new products to market. In the service – when analyzing satisfaction, assessing value of each customer, etc.
In addition, I would like to notice that such tools as Oracle BI enable to cover the problem of business intelligence at the tactical and strategic levels of management effectively. In this case, using of a single tool would provide high-quality synchronization of business goals, set before BI. The previous experience guarantees more effective using of the already proven BI-application.
Thank you so much for your attention and hope this article is of interest to you.
Elvira Golyak – Business Development Manager (LI page)
Elvira.Golyak@altabel.com | Skype ID: elviragolyak
Altabel Group – Professional Software Development
There is no doubt that 2012 will be another big year for BI and information management. In the article we`ve tried to gather what we suppose are the top BI trends for near future
Big Data → Need for Speed
The rise in volume (amount of data), velocity (speed of data) and variety (range of data) gives way to new architectures that no longer only collect and store but actually use data: on-demand or real-time BI architectures will replaces traditional datawarehouses. Successful business intelligence projects will need to consider Big Data as part of their data landscape for the value that it delivers. More and more organizations will look toward statistics and data mining to set strategic direction and gain greater insights to stay ahead of the pack.At the same time the BI user is expecting faster answers from their BI environment disregarding the fact that the size of data is increasing.
Shift from analytical BI to operational BI
Increased adoption of cloud and mobile BI encourage individuals to access their KPI dashboards (key performance indicators), more often. An operational dashboard works much like a car’s dashboard. As you drive, you monitor metrics that indicate the current performance of your vehicle and make adjustments accordingly. When the speed-limit changes, you check your speedometer and slow down, or when you see you are out of gas you pull over and fill-up. Likewise, an operational dashboard allows you to make tactical decisions based on current performance, whether it is chasing a red-hot lead or ordering an out-of-stock product.
Latest surveys showed that only 25% of employees in businesses that adopted BI had access to that tool. And that is not because they didn`t want to or didn`t need information, but because traditional BI tools have been too bulky and technical for that other 75% of employees to use.
As now organizations more and more are adopting cloud and mobile BI dashboards, this situation is likely to change. Business intelligence is heading towards simpler, more straightforward methods and tools..
An Agile approach can be used to incrementally remove operational costs and if deployed correctly, can return great benefits to any organization. Agile provides a streamlined framework for building business intelligence/data warehousing (BIDW) applications that regularly delivers faster results using just a quarter of the developer hours of a traditional waterfall approach.
It allows you to start a project after doing 20 per cent of the requirements and design that deliver 80 per cent of the project’s value. The remaining details are filled in once development is underway and everyone has a good look at what the challenges actually are.
BI going mobile
In a survey conducted by Gartner, it was found that by 2013 one-third of all BI usage will be on a mobile device, such as a smart-phone or tablet. BI users want to access their data anytime and anywhere. This puts a demand on both the backend of any BI solution (like datawarehouse appliances) but also on the frontend where information access and visualization must be possible.
BI going up to the Cloud
As Cloud computing continues to dominate the whole IT landscape, so BI also dominates in the Cloud . Throughout next few years adoption of cloud BI tools will be driven by a number of important factors. First, cloud-based solutions offer the advantage of being relatively simple and convenient to deploy. Second, cloud tools are more easily scalable to provide access to key performance indicators (KPIs) to everyone in your organization, no matter where they are or what device they are using. Lastly, continually improving security measures will put to rest any reservations businesses have with storing their sensitive data in the cloud.
We believe these above enumerated areas will grow over the next few years. Organizations will embrace the Agile approach, utilizing new tools and technologies to decrease delivery times and demonstrate substantial business value. As we put more data into the Cloud, big data will become standard. Data itself will be delivered to satisfy the desires of users, so access from mobile devices will dominate desk-based consumption. The businesses that embrace these new business intelligence trends, and take steps to change and adapt the way data is hosted, analyzed, utilized and delivered, will be the ones that grow and prosper in the near future.
And what are your predictions for the big business intelligence trends in the next few years? Do you agree/disagree with our predictions?