Category Archives: Data Governance
In honor of International Women’s Day 2015, Informatica is celebrating female leadership in a blog series. Every day this week, we will showcase a new female leader at Informatica, who will share their perspective on what it’s like to be a woman in the tech industry.
Senior Director, Global Customer Support
Women leaders bring a different perspective and skills that are essential to a company’s success. Women leaders are looked up as role models for other women starting their career, which attracts a diverse workforce.
Find balance in your work and home life so you are in a good position to “lean in” to your workplace, as Sheryl Sandberg wrote in her book, Lean In: Women, Work, and the Will to Lead.
Advice for other women:
Do your best and be bold. Make some compromises to ensure a good work-life balance. Be abreast of what is happening around your industry.
Thoughts about Informatica’s culture:
Next month I will be completing 17 years at Informatica. It all started off with a role in the support organization helping our customers. I had an opportunity to switch roles to the Quality Assurance team, which I led, and became a Senior Manager. Later, I got an opportunity to transition back into support organization, which I am a now the Senior Director of. Most of my career has been at Informatica. My colleagues and managers have been very supportive in helping me to attain the right work-life balance. My family also feels they are part of Informatica family.
Let’s face it, building a Data Governance program is no overnight task. As one CDO puts it: ”data governance is a marathon, not a sprint”. Why? Because data governance is a complex business function that encompasses technology, people and process, all of which have to work together effectively to ensure the success of the initiative. Because of the scope of the program, Data Governance often calls for participants from different business units within an organization, and it can be disruptive at first.
Why bother then? Given that data governance is complex, disruptive, and could potentially introduce additional cost to a company? Well, the drivers for data governance can vary for different organizations. Let’s take a close look at some of the motivations behind data governance program.
For companies in heavily regulated industries, establishing a formal data governance program is a mandate. When a company is not compliant, consequences can be severe. Penalties could include hefty fines, brand damage, loss in revenue, and even potential jail time for the person who is held accountable for being noncompliance. In order to meet the on-going regulatory requirements, adhere to data security policies and standards, companies need to rely on clean, connected and trusted data to enable transparency, auditability in their reporting to meet mandatory requirements and answer critical questions from auditors. Without a dedicated data governance program in place, the compliance initiative could become an on-going nightmare for companies in the regulated industry.
A data governance program can also be established to support customer centricity initiative. To make effective cross-sells and ups-sells to your customers and grow your business, you need clear visibility into customer purchasing behaviors across multiple shopping channels and touch points. Customer’s shopping behaviors and their attributes are captured by the data, therefore, to gain thorough understanding of your customers and boost your sales, a holistic Data Governance program is essential.
Other reasons for companies to start a data governance program include improving efficiency and reducing operational cost, supporting better analytics and driving more innovations. As long as it’s a business critical area and data is at the core of the process, and the business case is loud and sound, then there is a compelling reason for launching a data governance program.
Now that we have identified the drivers for data governance, how do we start? This rather loaded question really gets into the details of the implementation. A few critical elements come to consideration including: identifying and establishing various task forces such as steering committee, data governance team and business sponsors; identifying roles and responsibilities for the stakeholders involved in the program; defining metrics for tracking the results. And soon you will find that on top of everything, communications, communications and more communications is probably the most important tactic of all for driving the initial success of the program.
A rule of thumb? Start small, take one-step at a time and focus on producing something tangible.
Sounds easy, right? Well, let’s hear what the real-world practitioners have to say. Join us at this Informatica webinar to hear Michael Wodzinski, Director of Information Architecture, Lisa Bemis, Director of Master Data, Fabian Torres, Director of Project Management from Houghton Mifflin Harcourt, global leader in publishing, as well as David Lyle, VP of product strategy from Informatica to discuss how to implement a successful data governance practice that brings business impact to an enterprise organization.
If you are currently kicking the tires on setting up data governance practice in your organization, I’d like to invite you to visit a member-only website dedicated to Data Governance: http://governyourdata.com/. This site currently has over 1,000 members and is designed to foster open communications on everything data governance. There you will find conversations on best practices, methodologies, frame works, tools and metrics. I would also encourage you to take a data governance maturity assessment to see where you currently stand on the data governance maturity curve, and compare the result against industry benchmark. More than 200 members have taken the assessment to gain better understanding of their current data governance program, so why not give it a shot?
Data Governance is a journey, likely a never-ending one. We wish you best of the luck on this effort and a joyful ride! We love to hear your stories.
I’ve spent most of my career working with new technology, most recently helping companies make sense of mountains of incoming data. This means, as I like to tell people, that I have the sexiest job in the 21st century.
Harvard Business Review put the data scientist into the national spotlight in their publication Data Scientist: The Sexiest Job of the 21st Century. Job trends data from Indeed.com confirms the rise in popularity for the position, showing that the number of job postings for data scientist positions increased by 15,000%.
In the meantime, the role of data scientist has changed dramatically. Data used to reside on the fringes of the operation. It was usually important but seldom vital – a dreary task reserved for the geekiest of the geeks. It supported every function but never seemed to lead them. Even the executives who respected it never quite absorbed it.
For every Big Data problem, the solution often rests on the shoulders of a data scientist. The role of the data scientist is similar in responsibility to the Wall Street “quants” of the 80s and 90s – now, these data experienced are tasked with the management of databases previously thought too hard to handle, and too unstructured to derive any value.
So, is it the sexiest job of the 21st Century?
Think of a data scientist more like the business analyst-plus, part mathematician, part business strategist, these statistical savants are able to apply their background in mathematics to help companies tame their data dragons. But these individuals aren’t just math geeks, per se.
A data scientist is somebody who is inquisitive, who can stare at data and spot trends. It’s almost like a renaissance individual who really wants to learn and bring change to an organization.
If this sounds like you, the good news is demand for data scientists is far outstripping supply. Nonetheless, with the rising popularity of the data scientist – not to mention the companies that are hiring for these positions – you have to be at the top of your field to get the jobs.
Companies look to build teams around data scientists that ask the most questions about:
- How the business works
- How it collects its data
- How it intends to use this data
- What it hopes to achieve from these analyses
These questions were important because data scientists will often unearth information that can “reshape an entire company.” Obtaining a better understanding of the business’ underpinnings not only directs the data scientist’s research, but helps them present the findings and communicate with the less-analytical executives within the organization.
While it’s important to understand your own business, learning about the successes of other corporations will help a data scientist in their current job–and the next.
As we head into Strata + Hadoop World San Jose, Pivotal has made some interesting announcements that are sure to be the talk of the show. Pivotal’s move to open-source some of their advanced products (and to form a new organization to foster Hadoop community cooperation) are signs of the dynamism and momentum of the Big Data market.
Informatica applauds these initiatives by Pivotal and we hope that they will contribute to the accelerating maturity of Hadoop and its expansion beyond early adopters into mainstream industry adoption. By contributing HAWQ, GemFire and the Greenplum Database to the open source community, Pivotal creates further open options in the evolving Hadoop data infrastructure technology. We expect this to be well received by the open source community.
As Informatica has long served as the industry’s neutral data connector for more than 5,500 customers and have developed a rich set of capabilities for Hadoop, we are also excited to see efforts to try to reduce fragmentation in the Hadoop community.
Even before the new company Pivotal was formed, Informatica had a long history working with the Greenplum team to ensure that joint customers could confidently use Informatica tools to include the Greenplum Database in their enterprise data pipelines. Informatica has mature and high-performance native connectivity to load data in and out of Greenplum reliably using Informatica’s codeless, visual data pipelining tools. In 2014, Informatica expanded out Hadoop support to include Pivotal HD Hadoop and we have joint customers using Informatica to do data profiling, transformation, parsing and cleansing using Informatica Big Data Edition running on Pivotal HD Hadoop.
We expect these innovative developments driven by Pivotal in the Big Data technology landscape to help to move the industry forward and contribute to Pivotal’s market progress. We look forward to continuing to support Pivotal technology and to an ever increasing number of successful joint customers. Please reach out to us if you have any questions about how Informatica and Pivotal can help your organization to put Big Data into production. We want to ensure that we can help you answer the question … Are you Big Data Ready?
In our house when we paint a room, my husband does the big rolling of the walls or ceiling, I do the cut-in work. I am good at prepping the room, taping all the trim and deliberately painting the corners. However, I am thrifty and constantly concerned that we won’t have enough paint to finish a room. My husband isn’t afraid to use enough paint and is extremely efficient at painting a wall in a single even coat. As a result, I don’t do the big rolling and he doesn’t do the cutting in. It took us awhile to figure this out, and a few rooms had to be repainted while we were figuring it out. Now we know what we are good at, and what we need help with.
Payers roles are changing. Payers were previously focused on risk assessment, setting and collecting premiums, analyzing claims and making payments – all while optimizing revenues. Payers are pretty good at selling to employers, figuring out the cost/benefit ratio from an employers perspective and ensuring a good, profitable product. With the advent of the Affordable Healthcare Act along with a much more transient insured population, payers now must focus more on the individual insured and be able to communicate with the individuals in a more nimble manner than in the past.
Individual members will shop for insurance based on consumer feedback and price. They are interested in ease of enrollment and the ability to submit and substantiate claims quickly and intuitively. Payers are discovering that they need to help manage population health at a individual member level. And population health management requires less of a business-data analytics approach and more social media and gaming-style logic to understand patients. In this way, payers can help develop interventions to sustain behavioral changes for better health.
When designing such analytics, payers should consider the following key design steps:
- Extend data warehouses to an analytics appliance
- Invest in a big data platform to absorb patients’ social data
- Build predictive analytics for patient behavior
- Bridge collaborative and behavioral analytics with claims to build revenue and profitability
Due to payers’ mature predictive analytics competencies, they will have a much easier time in the next generation of population behavior compared to their provider counterparts. As clinical content is often unstructured compared to the claims data, payers need to pay extra attention to context and semantics when deciphering clinical content submitted by providers. Payers can use help from vendors that can help them understand unstructured data, individual members. They can then use that data to create fantastic predictive analytic solutions.
Achieving and maintaining a single, semantically consistent version of master data is crucial for every organization. As many companies are moving from an account or product-centric approach to a customer-centric model, master data management is becoming an important part of their enterprise data management strategy. MDM provides the clean, consistent and connected information your organizations need for you to –
- Empower customer facing teams to capitalize on cross-sell and up-sell opportunities
- Create trusted information to improve employee productivity
- Be agile with data management so you can make confident decisions in a fast changing business landscape
- Improve information governance and be compliant with regulations
But there are challenges ahead for the organizations. As Andrew White of Gartner very aptly wrote in a blog post, we are only half pregnant with Master Data Management. Andrew in his blog post talked about increasing number of inquiries he gets from organizations that are making some pretty simple mistakes in their approach to MDM without realizing the impact of those decisions on a long run.
Over last 10 years, I have seen many organizations struggle to implement MDM in a right way. Few MDM implementations have failed and many have taken more time and incurred cost before showing value.
So, what is the secret sauce?
A key factor for a successful MDM implementation lays in mapping your business objectives to features and functionalities offered by the product you are selecting. It is a phase where you ask right questions and get them answered. There are few great ways in which organizations can get this done and talking to analysts is one of them. The other option is to attend MDM focused events that allow you to talk to experts, learn from other customer’s experience and hear about best practices.
We at Informatica have been working hard to deliver you a flexible MDM platform that provides complete capabilities out of the box. But MDM journey is more than just technology and product features as we have learnt over the years. To ensure our customer success, we are sharing knowledge and best practices we have gained with hundreds of successful MDM and PIM implementations. The Informatica MDM Day, is a great opportunity for organizations where we will –
- Share best practices and demonstrate our latest features and functionality
- Show our product capabilities which will address your current and future master data challenges
- Provide you opportunity to learn from other customer’s MDM and PIM journeys.
- Share knowledge about MDM powered applications that can help you realize early benefits
- Share our product roadmap and our vision
- Provide you an opportunity to network with other like-minded MDM, PIM experts and practitioners
So, join us by registering today for our MDM Day event in New York on 24th February. We are excited to see you all there and walk with you towards MDM Nirvana.
Informatica users leveraging HDP are now able to see a complete end-to-end visual data lineage map of everything done through the Informatica platform. In this blog post, Scott Hedrick, director Big Data Partnerships at Informatica, tells us more about end-to-end visual data lineage.
Hadoop adoption continues to accelerate within mainstream enterprise IT and, as always, organizations need the ability to govern their end-to-end data pipelines for compliance and visibility purposes. Working with Hortonworks, Informatica has extended the metadata management capabilities in Informatica Big Data Governance Edition to include data lineage visibility of data movement, transformation and cleansing beyond traditional systems to cover Apache Hadoop.
Informatica users are now able to see a complete end-to-end visual data lineage map of everything done through Informatica, which includes sources outside Hortonworks Data Platform (HDP) being loaded into HDP, all data integration, parsing and data quality transformation running on Hortonworks and then loading of curated data sets onto data warehouses, analytics tools and operational systems outside Hadoop.
Regulated industries such as banking, insurance and healthcare are required to have detailed histories of data management for audit purposes. Without tools to provide data lineage, compliance with regulations and gathering the required information for audits can prove challenging.
With Informatica, the data scientist and analyst can now visualize data lineage and detailed history of data transformations providing unprecedented transparency into their data analysis. They can be more confident in their findings based on this visibility into the origins and quality of the data they are working with to create valuable insights for their organizations. Web-based access to visual data lineage for analysts also facilitates team collaboration on challenging and evolving data analytics and operational system projects.
The Informatica and Hortonworks partnership brings together leading enterprise data governance tools with open source Hadoop leadership to extend governance to this new platform. Deploying Informatica for data integration, parsing, data quality and data lineage on Hortonworks reduces risk to deployment schedules.
A demo of Informatica’s end-to-end metadata management capabilities on Hadoop and beyond is available here:
- A free trial of Informatica Big Data Edition in the Hortonworks Sandbox is available here .
As Valentine’s Day approaches and retailers & restaurants prepare to sell millions of cards, teddy bears, bottles of champagne and for the lucky few, some expensive jewels, I started to think about my love affair with data and the many ups and downs we had over the years!
Our first date together was arranged by a third party and everything I was told was from their perspective. I had many questions; could I trust data, was I getting the complete picture from the third party, would we be compatible and ultimately “fit for purpose” or would data break my heart!
As we shared information we were both apprehensive, not everything was fitting together, there were gaps in data’s story, and I just could not make an informed decision, this lead to mistrust between the two of us. I stated to ask other friends and associates for their information and tried to reconcile with my view of data. I wanted it to work but what could I do?
A close friend, Stewart, recommended I get some professional advice to help with my issues with data and pointed me towards Doctor Rob, one of the leading authorities on data, specialising in data governance.
The first bit of advice Doctor Rob gave me was; it should never have been about data, the dream must be about your long term goals together, your commitment to get it right, your interactions with others in your circle of friends and dependents.
The second piece of advice was to decide what roles and responsibilities each of us would take on in the relationship. Evaluate if we have the right skills or do we need external support or training to succeed.
While we are still on our journey together data and I are now in a long term committed relationship and look forward to many years on Cloud 9.
Now all I have to decide is will I go to Tiffany’s or Claire’s for that piece of jewellery!
The signs that healthcare is becoming a more consumer (think patients, members, providers) driven industry are evident all around us. I see provider and payer organizations clamoring for more data, specifically data that is actionable, relatable and has integrity. Armed with this data, healthcare organizations are able to differentiate around a member/patient-centric view.
These consumer-centric views convey the total value of the relationships healthcare organizations have with consumers. Understanding the total value creates a more comprehensive understanding of consumers because they deliver a complete picture of an individual’s critical relationships including: patient to primary care provider, member to household, provider to network and even members to legacy plans. This is the type of knowledge that informs new treatments, targets preventative care programs and improves outcomes.
Payer organizations are collecting and analyzing data to identify opportunities for more informed care management and segmentation to reach new, high value customers in individual markets. By segmenting and targeting messaging to specific populations, health plans generate increased member satisfaction and cost effectively expands and manages provider networks.
How will they accomplish this? Enabling members to interact in health and wellness forums, analyzing member behavior and trends and informing care management programs with a 360 view of members… to name a few . Payers will also drive new member programs, member retention and member engagement marketing and sales programs by investigating complete views of member households and market segments.
In the provider space, this relationship building can be a little more challenging because often consumers as patients do not interact with their doctor unless they are sick, creating gaps in data. When provider organizations have a better understanding of their patients and providers, they can increase patient satisfaction and proactively offer preventative care to the sickest (and most likely to engage) of patients before an episode occurs. These activities result in increased market share and improved outcomes.
Where can providers start? By creating a 360 view of the patient, organizations can now improve care coordination, open new patient service centers and develop patient engagement programs.
Analyzing populations of patients, and fostering patient engagement based on Meaningful Use requirements or Accountable Care requirements, building out referral networks and developing physician relationships are essential ingredients in consumer engagement. Knowing your patients and providing a better patient experience than your competition will differentiate provider organizations.
You may say “This all sounds great, but how does it work?” An essential ingredient is clean, safe and connected data. Clean, safe and connected data requires an investment in data as an asset… just like you invest in real estate and human capital, you must invest in the accessibility and quality of your data. To be successful, arm your team with tools to govern data –ensuring ongoing integrity and quality of data, removes duplicate records and dynamically incorporates data validation/quality rules. These tools include master data management, data quality, metadata management and are focused on information quality. Tools focused on information quality support a total customer relationship view of members, patients and providers.
The latest North American B2C e-commerce market report is out now. For my followers I took the freedom to summarize some “Magnificent Seven Facts on B2C eCommerce in North America” in a short blog. The report covers United States, Canada and Mexico, but as well comparisons to Europe and Asia. According to this report, North American B2C e-commerce market is expected to reach $494.0 billion in 2014.
The Magnificent Seven Facts
- 122.5 million households in North America
- 336 million internet users in North America
- North America makes up 29.2% of the total global online sales ($1,552.0bn) in 2013.
- In terms of global B2C e-commerce, North America ranked third in 2013, behind Asia-Pacific and Europe
- North American consumers spent on average$2,116 online in2013. This is significantly above the global average of €1,280.
- With an average spending per e-shopper of $2,216, American consumers spent most online in2013. Canadians ranked second with an average spending of $1,577, while Mexican e-shoppers on average spent $1,133 online in2013.
- Canadians are more likely to shop mobile
Mobile Commerce: Canada Leads the Pack
Within North America, mobile commerce is most popular in Canada, with more than half of the online purchases per week being made through a mobile device. At 38.2%, US Americans still make their mobile purchases in the safe surroundings of their homes.
What are the barriers preventing mobile purchasing?
Free downloads available now
Would you like to find out more about global e-commerce? The free light versions of our Regional/Continental Reports can be downloaded here.