Data Analytics Archives - Page 2 of 6 - Management Information Analysis

Your Data on Call . . . Virtually

June 9, 2016 by MIAWebAdmin

It’s a growing trend: more and more, business and healthcare management applications live outside of the firewall. Sure, some applications still live in-house, but others have moved to the cloud. Still others were replaced with SaaS options.

In the past, business software focused on function over form. It wasn’t usually pretty, but it got the job done. But, a funny thing happened when mobile apps and cloud-based consumer software became popular. Users realized something: Software doesn’t have to be boring or confusing.

New software has been developed with integration in mind. Software that can be integrated with existing systems via an accessible API and web services can ensure that the value of both the new and existing systems is maximized. Get on board and you are empowered to drive success.

Take a look at these changes as choices that are available—and affordable.

In our dreary past, data integration requests were time-consuming since ETL tools process in batches. Today, the demand for more agility accompanied by a shrinking budget pushes savvy information management and planning teams to search for an alternative.

Now you have the option to point your efforts in a new direction: data virtualization. Rather than copy and move data, the technology allows you to keep the tools your team currently has, abstracts data from multiple sources, and creates a virtual view for the user through a Web portal.

This enables users to quickly query, share, and—most importantly—integrate data, whether it resides in flat files, an Oracle database, or on an SQL Server.

According to Forrester, data virtualization can also be relatively inexpensive compared with traditional data integration methods, such as database consolidation.

Press the pause button for a moment, sit with your data management and analytics thought partner, and decide on which easy-to-use product meets your important criteria. A truly competitive enterprise needs a contemporary, on-call set of analytics that supports big data and everything else and is based on a streaming architecture. This is the era of visual analytics at the speed of thought.

You can bring your data to its highest and best uses, or you can let it languish while you guess and your competitors pass you on the back stretch. And you DO NOT have to bet the farm and the horses to get where you want to go with your data assets. We are a good match to be your analytics thought partner and trusted virtual team that delivers your data to your dashboards.

Reminder: in today’s mobile ecosystem, always secure your portals and data!

Our Austin, Texas location keeps us at the epicenter of planning analytics and data-driven innovation and keeps our global capabilities and services at the forefront of our industry.

Email us at kcerny@mia-consulting.com or call us at 512-478-3848 to start a friendly, productive conversation.

Data Virtualization Is Data Integration Streaming

June 3, 2016 by MIAWebAdmin

Data virtualization performs many of the same transformation and quality functions as traditional data integration (Extract-Transform-Load), data replication, data federation, Enterprise Service Bus (ESB), etc., but it leverages modern technology to deliver real-time data integration at lower cost, with more speed and agility.

Data virtualization is synonymous with information agility: it delivers a simplified, unified, and integrated view of trusted business data in real time or near real time as needed by the consuming applications, processes, analytics, or business users.

It also integrates data from disparate sources, locations, and formats without replicating the data, creating a single, “virtual” data layer that delivers unified data services to support multiple applications and users. The result is faster access to all data, less replication and cost, and more agility to change.

A truly competitive enterprise needs a contemporary, on-call set of analytics that supports big data and everything else and is based on a streaming architecture. This is the era of visual analytics at the speed of thought.

You bring your data to its highest and best uses or you can let it languish while you “guess” and your competitors pass you on the back stretch. And you DO NOT have to bet the farm and the horses to get where you want to go with your data assets. We are a good match to be your analytics thought partner and trusted virtual team that delivers your data to your dashboards.

Our Austin, Texas location keeps us at the epicenter of planning analytics and data-driven innovation and keeps our global capabilities and services at the forefront of our industry.

Email us at kcerny@mia-consulting.com or call us at 512-478-3848 to start a friendly, productive conversation.

Get Your Data Out of Those Hobbit Holes!

May 27, 2016 by MIAWebAdmin

Whether it’s revenue-cycle management in healthcare delivery or back-office forms administration in financial services sectors, the process of getting usable data out of desktop silos and into secure cloud warehouse continues to creep along. But really, folks, it must get handled.

The shared anxiety around data risk will unify leadership and IT teams as the new crop of solutions enable simpler administration, transparent governance, and agile collaboration.

The movement will be further accelerated as more entities are seeing elastic cloud architectures as the mainstay of big data and intelligence standardization decisions. In fact, this will become the litmus test for Chief Data Officers and CTOs: if the solution doesn’t have a built-in elastic architecture, it won’t be fully deployed.

Here’s another thing: in general, we will see a major movement to adopt cloud data storage in the financial service industry. In fact, one of the top five financial institutions will announce a cloud-first or cloud-only IT philosophy –adopting one or more of the big three players.

If the CIA is doing it, why can’t the banks?

Adapt, die, or outsource?

Data preparation will be a critical capability of subject matter experts who, traditionally, relied on others to get data ready for them. In order to transform data into information on demand, people doing risk analysis, customer targeting, security monitoring, marketing, or sales operations will need the necessary skills and tools to handle self-service data preparation at scale.

Across all of these changes in how we manage our data assets, we see outsourcing the ETL process and teaming with talented analyst groups as practices that will cost-effectively accelerate your big data and analytics priorities. Outsourcing is now mainstream.

Our Austin, Texas location keeps us at the epicenter of software engineering innovation and keeps Management Information Analysis’ global capabilities at the forefront of our industry.

Call us to start a friendly and productive conversation. 512-478-3848

That’s all for today, but please stay tuned to this Management Information Analysis and our Planning Analytics blog channels for more actionable insights.

Meet the Future of ETL and Custom Applications

May 20, 2016 by MIAWebAdmin

We’re now into the meat of 2016, and if you take a look around our business and healthcare ecosystems, you’ll see that a number of positive changes are accelerating across the custom applications development of our information management worlds.

Here is some of the information we have parsed from trusted and knowledgeable sources:

Companies are adopting NoSQL policy for their critical operations and cloud computing their data in 2016. The era of big data is upon us, with Windows 10 being a predecessor of an online OS (or a beta version, which will be massively updated in the future).
- Android is preparing their counterpart for Win 10 based on Chrome and Spark, conquering new horizons as cloud hosting becomes more functional and popular each day.
Software future trends are firmly within the cloud. Just analyze the job listings: whenever you see any big company involved in software-development hiring, they say, “cloud experience would be an advantage.”
- We assume you will agree with the statement that 80 percent of resources (be it time, money, or developer’s effort) spent on ANY new custom application is spent on ETL process. Regardless of the coding language that the app is built on and the trends that software follows, you have to gather the raw data, transform it into operable information, and load it into the database so your custom applications can process it.
Current software development trends explicitly show that current data analysis systems will not cope with big data efficiently enough. Issues with scalability, simultaneous processing of different data sources, and efficient data transformation pose big threats and require an efficient solution strategy. One possible solution might be Red Hat’s data virtualization technology.
- Therefore, the company that will show the most efficient way of overcoming the ETL issues can be forming new software trends in big data for the years to come.

Add to this the possibility of packing it in containers, thus unifying the tools and making the app a multipurpose cross-platformer, and only the sky will be the limit.

Our Austin, Texas location keeps us at the epicenter of software engineering innovation and keeps Management Information Analysis’ global capabilities at the forefront of our industry.

Call us to start a friendly and productive conversation. 512-478-3848.

Do Anything With Your Data – But Please Protect It

May 13, 2016 by MIAWebAdmin

It’s May. Is it time to ask about outsourcing your ETL processes?

An automated ETL tool typically provides a visual environment or platform that lets you see large parts of the ETL process (e.g. where the data is coming from and going, which calculations are performed on it, etc.) in ways that old code practices—however carefully crafted and documented—will never be able to replicate.

As we have offered many times over the past 18 months, the sooner and more efficiently you get your data out of silos, the better able you are to make analytical and predictive uses of your data. Now that always leads to one of the biggest benefits of big data.

Here are a few big data benefits:

Predictive modeling, which involves running simulations to predict the outcome of altering variables in a dataset, is one of those rewards at the end of your data rainbow.

With huge amounts of data from many different data points, the relationships between different variables can be examined in detail. This has proven advantageous in many circumstances, where analysts have found that tweaking a certain variable had unexpected consequences or outcomes.

Big data can highlight dangers looming on the horizon by showing what the likely consequences of a path of action will be. This has extended into the physical world, where machinery fitted with sensors that constantly feed data on their operations are becoming widespread across the industry.

Your big data systems can even build up an extensive understanding of how a machine works and when it is likely to go wrong, meaning that repairs can be scheduled, reducing costly downtime to a minimum. Flaws in the design or manufacturing process can be identified at an early stage.

Data always contains surprises. Tailor transformations to any event or field with our custom ETL Plus service. Explore your data in real-time, write alerts, and get notifications. Get your data out of silos, off other servers, and into your agile data management and planning streams.

And protect it.

As mobile computing advances, information management leadership will be called upon to safeguard equipment, data, and applications that employees will be operating at any time and from anywhere.

To accomplish this, your analysts must implement security systems for mobile and IoT applications that must be agile, robust, and able to function within, at, and beyond the edge of the enterprise network. Equally important will be aggressive policy development and training of employees, who can often be a leading source of mobile computing security abuse.

These devices are used externally as well as internally within companies. With the amount of time that a mobile device is used off premises, risks of device loss, data loss, or security breaches escalate.

So, too, does the risk of devices being misused by those who are both authorized and unauthorized to use them. Latch on to a partner who can accelerate your data transformation, making your data visual, usable, and immediately more agile!

Our Austin, Texas location keeps us at the epicenter of software engineering innovation and keeps Management Information Analysis’ global capabilities at the forefront of our industry.

Call us to start a friendly and productive conversation. 512-478-3848.

Two Big Data Trends in 2016 to Make You Stronger

January 16, 2016 by miawebadmin

We’re excited to be in the curl of the big data wave and helping our clients maximize their data assets this year. Our team is really grooved into what’s the best and highest use of a data analyst’s skills, talent and time and then where and how we can deliver the biggest ROI for your ETL Plus and custom apps development investment dollars.

Take a look at these and be sure to work them into your CIO inbox!

1. The number of options for “preparing” end users to discover all forms of data grows.

Self-service data preparation tools are exploding in popularity. This is in part due to the shift toward business-user-generated data discovery tools such as Tableau that reduce time to analyze data. Business users now want to also want to be able to reduce the time and complexity of preparing data for analysis, something that is especially important in the world of big data when dealing with a variety of data types and formats. We’ve seen a host of innovation in this space from companies focused on end user data preparation for Big Data such as Alteryx, Trifacta, Paxata and Lavastorm while even seeing long established ETL leaders such as Informatica with their Rev product make heavy investments here.

2. The buzzwords converge! IoT, Cloud and Big Data come together

The technology is still in its early days, but the data from devices in the Internet of Things will become one of the “killer apps” for the cloud and a driver of petabyte scale data explosion. For this reason, we see leading cloud and data companies such as Google, Amazon Web Services and Microsoft bringing Internet of Things services to life where the data can move seamlessly to their cloud based analytics engines.

Though these two changes and trends may seem disparate, they’re linked by the need to work with data quickly and conveniently. As Big Data changes and new ways of working with that data pop up, the details shift, but the song remains the same: everyone’s a data analyst, and there’s never been a more exciting job.

ETL and Data Management Trends

December 16, 2015 by miawebadmin

Two ETL and data management trends happened this year.

1. Data Storytelling

Information only begins to come to life if a story is told with it. We’re all familiar with the development of “human interest” stories in journalism. News and facts are hung together on human experiences and emotions.

Some people refer to data storytelling as the next step in the development of data visualization. Understandably, because, on the basis of visualized data, the user gains more and more insight into both what the data can do and the story behind the data. Some software vendors now already supply the capacity to apply a story line to a data visualization. It’s an interesting development.

It isn’t yet completely clear quite where storytelling should be put on the menu with discovery, exploration, visualization and data presentation. It’s also debatable whether existing Business Intelligence tools are able to improve communication about data. And isn’t it actually more about story finding? This may appear to be a semantic issue, but that’s far from the case. Naturally, ‘Storytelling’ sounds OK, but it’s about discovering the story behind the data, not so much about recounting it.

2. Shortage of Data Scientists

And the analysts who can extract, transform and load data from legacy systems into new-generation warehouses, formats and dashboards. Bringing different kinds and types of data together creatively, obtaining previously unimagined insights and translating them into practical issues remains the work of human beings. The exponential growth and availability of data, coupled with the ever growing need for analytics ensures that the existing shortage of data scientists will continue to rise. A good data scientist understands statistics, data blending and data visualization.

Do you see why you need a strategic partner that is an extension of your team?

We can help you extract, transform and load your data into meaningful sets, mobilize and monitor your predictive HR trends, measure progress toward a set of quantitative goals, flag shifts in your markets or financial operations and even lift your customer experiences to a higher level. Whew, that’s saying a lot. Or is that just our story?

Call us to start a neutral and friendly conversation that can enhance your data management investment while you “go mobile” and make savvy asset management decisions. 512 478 3848.

ICD-10 Implementation is Not Top Challenge in Healthcare

October 2, 2015 by miawebadmin

A comprehensive and well-thought-out big data analytics strategy can help healthcare providers navigate difficult transition from traditional reimbursement to population health management and value-based care. Most healthcare executives have not been trained to handle the scope of the business shift now being demanded of healthcare organizations, and that impact trickles down to those in the analytics department.

The good news is that this type of leadership can be learned; while it can’t be achieved overnight, this transition in analytics must happen quickly if success is the desired outcome.

According to a recent (September 23, 2015) blog post by J. Bryan Bennet titled “Top Challenges to Analytics in Healthcare? Not Technology”, this finding became clear in a study conducted by the Healthcare Center of Excellence this summer, which sought to determine what are perceived to be the top challenges facing analytics.

The study reveals the importance of executive leadership skills in bringing about support of analytics and the extent to which findings from analytic efforts are incorporated into how organizations change and adapt. This aspect of leadership, while learnable, needs to happen quickly if organizations want to achieve the desired incomes from their forays into analytics.

The challenges were classified into 10 categories – analytic tools, change management, costs, data management, education, integration, leadership, process, talent and technology. While the challenges facing healthcare analytics implementations may not surprise anyone, the order of magnitude, related to the number of times they were mentioned may be surprising.

The top three categories were leadership, mentioned by 29 percent; data management, mentioned by 18 percent; and talent, mentioned by 14 percent. The technology and tools weren’t perceived as being a problem – in fact, technology was mentioned by only 5 percent, analytics tools and process, both at 3 percent.

But please notice; data management and talent are the screaming issues of many healthcare delivery organizations in the U. S. today . . . the day ICD – 10 went into effect.

If healthcare leadership chooses to accelerate its learning curve up to levels needs to exceed the coming Medicare standards for reimbursement and their own revenue cycle management benchmarks, they are wise to look to proven teams not under their tent.

Planning analytics and data management tools are just two of our sweet spots. Our custom application development expertise allows our analysts to mix and match data sets as needed. We can blend internal with external data sources to establish historical trends and project patient need and demand, which are the backbone of any feasibility study.

Additionally, we can help you monitor trends, measure progress toward a quantitative goal or flag shifts in your market or financial operations. Take a look at one of our hospital success stories. And then call us to start a conversation that can enhance your data management investment while you make savvy delivery location decisions. 512 478 3848

Will You Tame The Monster? One Bite At A Time?

September 21, 2015 by miawebadmin

We have talked before about the roles of the ETL developer and ETL Plus* teams and how transforming internal data and external warehoused data into useful business intelligence seems to be an insurmountable challenge on some days. The monster that we encounter certainly has been described many times. The analysts spend up to 80% of their time, energy and talent on getting the data into a usable shape and on a secure platform. And they are really not very good doing this. So productivity takes a dive. And you’re locked into the costs.

Extraction is the only first step. That’s obvious. But transformation is the tipping point to usability.

Data transformation is the process of changing the format of data so that it can be used by different applications. This may mean a change from the format the data is stored in into the format needed by the application that will use the data. This process also includes mapping instructions so that applications are told how to get the data they need to process.

The process of data transformation is made far more complex because of the staggering growth in the amount of unstructured data. A healthcare application such as a patient relationship management process has specific requirements for how data should be stored. The data is likely to be structured in the organized rows and columns of a relational database. Data is semi-structured or unstructured if it does not follow rigid format requirements.

The increase in volume of data is one of the most significant trends in healthcare. Analysts at the McKinsey Global Institute predict that the average hospital will be closing in on having a petabyte of patient data by 2015 and most of this data will be unstructured, such as radiology and imaging scans. This massive volume of data, coupled with the challenges of storing and sharing unstructured data, will likely lead to the implementation of patient data warehoused at most hospitals.

If you choose to engage a specialist partner, like our teams at Management Information Analysis, you, quickly accelerate and elevate your decision-making advantages by using a proven resources without adding to your hard or operational costs and overhead.

By providing a competent, affordable solution to these data challenges, you can then start to use data warehouses to reduce the number of unnecessary or repeated tests and treatments.

Personalized medicine is growing trend. As individual patient data becomes more accessible and the means to analyze it become easier, treatment protocols will move from a one-size-fits-all model to treatments based on each patient’s unique medical history and current medical issues. Analysis of genetic markers also will increase, allowing physicians to step in earlier to prevent disease or reduce its impact on patients. They also will be able to more precisely target treatment for diseases that are expensive to treat.

Prevention is another trend that is on the rise. By using big data, physicians can develop a better insight on patterns of factors, both genetic and behavioral, that increase patients’ risk of disease. Using this information, physicians can then recommend medications or guide patients to make lifestyle changes to reduce their overall risk of disease. Disease prevention represents a huge potential cost savings of $70 to $100 billion, according to the McKinsey Global Institute.

Villanova University recently affirmed in a blog article that data can play a key role in managing more than patient treatment. Hospitals are also looking to big data in order to manage logistics such as patient throughput, improve patient flow in triage and make better predictions based on facility population level.

Using big data for these types of analyses, hospitals would know optimal patient discharge times to make best use of bed space without sacrificing patient outcome. Physicians could more accurately prioritize and treat patients in emergency and trauma cases and generally improve patient outcomes while reducing costs by providing the right treatment at the right time.

You can takes steps now to get your data into the shape of intelligence. And we can facilitate that process. You may not know that we can unbundle the ETL Plus* process to access your data and manage the transformation process precisely to your specs and targeted predictive outcomes.

Our custom application development expertise allows our analysts to mix and match data sets as needed. We can blend internal with external data sources to establish historical trends and project need and demand, which are the backbone of any feasibility study. Tame the monster! Talk to us.

Enable a More Efficient, Scalable Reporting Process

May 25, 2015 by miawebadmin

Typically, hospital or group practice executives meet to determine the categories of healthcare data they need to track progress toward strategic goals. They may already have a process in place for getting financial data. But now, with new value-based purchasing pressures requiring clinical and financial data, organizations suddenly are tasked with getting more data than ever before. Questions may arise, such as:

Where do I start?
Who do I approach for the data?
Where is the data stored?
How do I get at the data after I’ve found it?
How do I compile and make sense of it?

Locating the right people with the right data – whether it’s a single person who updates an Excel document or a team overseeing a database – is a time-consuming, manual process. Staff can spend a lot of time setting up this process to gather and compile data to keep executives up to date.

There is a better way!

We provide the quantitative analysis needed to make informed decisions. Our ETL Plus* and custom application development skills allow us to effectively use internal and external data to analyze historical trends and project future market changes. We can also establish a process for identifying shifts in your market or operations or help you monitor progress toward a quantitative goal.

We are proven professionals that support you with data integration services, custom application development, and enterprise and strategic planning solutions.

Call or email us today to start a conversation – and increase the value of your data-driven decisions.