Talking About business performance, you can hardly ignore the value of Data Warehousing. Data mining and strategic toolsets are the quintessential assets. This seems to be the way forward for thriving Intelligent Businesses.
“Oracle brought in 3.6 billion U.S. dollars from the sale of data warehouse management software in the year of 2014.” This figure implies, organizations are just vying for an intelligent data warehouse, where do you stand?
Today’s business scenario is pretty much perceivable thoroughly and your data is the most useful asset your business can rely on.Talking about Competitive advantage, the next thing that pops up is the information that matters. Put it in another way, you will instantly realize how effective decision support systems can get for businesses. It makes complete sense to invest in a data warehouse. Ultimately, your business is a winner when you can deliver projects that can meet requirements precisely.
A Word about Data Warehousing that Drives Business Intelligence
You will agree that a structured data store is a key to an intelligent business.Here’s the real challenge.
How exactly do you get to the core of such an information system?
Well, you have to ask yourself a few questions:
- How do I ensure, that the critical decision-making data is free from any duplication, inconsistencies or inaccuracies?
- How do I get the right view of my customers and supply chain all along?
- How do I ensure that my reports are derived from time-sensitive data, making them reliable in the true sense?
- Is my analysis related to sales, performance, and risks viable? Is change management a painless process, without having to clean, scrub and reorganize the silos of data?
This is just the tip of the iceberg. Getting the right link that makes sense of your data is a learning process for your business.
When Data is Not as it Should be, Business Suffers Down to the Department Level
Your data inevitably comes from multiple sources, reconciling this information into a consistent whole can be challenging. Sometimes, businesses might not get the right way to deal with this data and derive actionable insights, and finally decisions from it.
The result: Widespread chaos and complexity.
The effect: Issues that affect you exponentially, especially when your business expands through geographic boundaries.
When your data loses integrity, your sales and marketing impact directly. You end up with an inefficient supply chain, and your products lack coherence. Eventually, they do not meet customer demands, thus can’t keep the pace with the vagaries of the market.
Some of the largest corporates have suffered unfathomable challenges due to operational inefficiencies. Businesses’ have reported low growth rate and profitability, and this can only be rescued by a thoughtful data warehousing approach:
- Europe’s financial services group was overcome by administrative and sales challenges when Infosys provided a scalable data warehouse architecture to accommodate their transaction volume, and therefore increase growth rate.
- Diverse data sources and customer touch points were making customer retention and growth a challenge for a leading bank in the United States. Xoriant data warehouse helped them to achieve goals in terms of customers’ lifetime value.
- Similar challenges related to the implementation of a customer data mart, housing terabytes of complex data were accomplished through Arbutus Data Warehousing and proved transformational.
- Data warehousing and reporting built for DHL by Capgemini helped raise operational efficiencies, reduce technology costs, and execute critical decisions with confidence.
What your business requires, data you can trust, and intelligence that imparts authority to your business.
This is How the Business World Sees Data Warehousing and Business Intelligence
The amount of research that has gone into the specifics of data warehousing, gives you multiple dimensions in implementing the strategy that will suit your business needs in the long run.
Take a look at the Information Week survey to start our mighty search on the kind of Intelligence your business might need in future.
Exploring, how businesses currently view information and intelligence in the big data era can be insightful for you too.
In this survey, 384 businesses concentrated around North America, disclosed how they deployed Analytics and Business Intelligence.
- The trend seems to be inclined towards companies, opting for multiple products in combination. For the same reason, organizations that were relying on a single solution came down from 35% to 28% in a single year.
- On the reverse side, use of multiple products has increased from 16% to 21%.
- Hadoop had been particularly popular among firms, with 7% more businesses opting for the big fish.
When setting out to consider, the best way to implement data warehousing, look for options in the cloud and Hadoop. These could be the main areas for exploration.
The Cloud and the Data Warehouse —a Skeptical Proposition on the Grounds of Security
With most of the businesses looking to cut costs, the cloud could be the best and most efficient solution, to implement your data warehousing initiative in a short period. The only glitch relates to the security concerns surrounding sensitive business data. The struggle here is to find the best solution to transfer and store data in the cloud. Amazon Redshift seems to be the path breaking initiative in this area. They have had a good hang of managing the cloud so far.Sharing this space with Amazon, we have Google, HP, and IBM.
But here’s the catch.Gartner is not too happy with the progress, not even with the efforts of technology giants, trying to draw warehouses inside the cloud spaces.Gartner’s dissatisfaction on Cloud IaaS spurs from the service level agreements, which are designed around the requirement of engaging multiple availability zones. Such an arrangement only spells extra costs to the business.
Another example is the SLA offered by Amazon web services. Their guarantee is only 99.9% uptime, plus only a partial refund of customer bill for the costs incurred during downtime. In contrast, Dimension Data, for that matter, guarantees 100% uptime and 100% refund. That sounds especially reassuring for businesses, taking data warehousing to the cloud level on a serious note.
So What’s the Big Deal about Hadoop and NoSQL?
Closely related to the data warehouse discussion is the viability of Hadoop. Do you see it as an alternative, an extension of the data warehousing approach, or are the two completely divergent technologies?
Our tech geeks have a few perspectives worth sharing:
- While most businesses rely on using a hybrid data approach, Hadoop could be more effective, when combined with a data warehouse. This would take care of processing complex data at low costs for relevant competitive insights.
- As per TDWI best practices report on Hadoop, most users see it as an extension to the organization’s data warehouse, rather than as a replacement. Hadoop is best deployed as an advanced analytical tool, while reporting is more closely identified with a data warehouse architecture.
- According to the joint report by Teradata and Cloudera, there are specific scenarios when Hadoop works best, and for others, Data warehouse could be the best option. Among the recommendations highlighted in the report, a data warehouse approach might work best, when security and regulatory compliance is the priority. On the other hand, complex processing logic and unstructured data are handled best using Hadoop. Both technologies seem to do well, even with 1000s of concurrent users and processor intensive executions.
What Must You Evaluate at the Core of Intelligent Data Warehousing
Data Quality—It could be a barrier to your success
The most important and critical element of a data warehouse is data quality. Accurate, complete and consistent data helps to prevent fragmentation. To ensure success with your data strategy, ensure data is free from duplicates and conforms to standards in your particular business domain. What you need in today’s business world is a robust data infrastructure across the enterprise that ensures consistency and accuracy of data.
Innovation and Experimentation―play the game well—as with any analytics and BI approach, innovation and experimentation are at the top of the list. Cloud, Big data, mobile and the data warehouse – all collectively favor experimentation and innovation for intelligent decision-making
Master Data Management—the Imperative Discipline for Today’s Business—Master Data Management (MDM) is the key to intelligent information that provides a single point of reference for ensuring your data is authoritative and can meet unique business challenges over time
Have You Experimented with Data Warehousing? Why not Share a Thought.
Most businesses are experimenting with their data strategies. So should you.
There is no right answer. But with practice, you will certainly get to the right blend of processes and strategies and guarantee a much more intelligent business than before.
Share your insights, your roadblocks and how you resolved them to be a data leader.