Does your decision-making process need an overhaul? In 2015, over 60% of the decisions made by companies were still based on ‘intuition’ or ‘experience’ of their executive team. With the rise of big data, it is imperative that we make use of such a valuable asset to make fact-based decisions and not just provide an opinion. This means that we need to become data-driven, of course this is easier said than done. It requires more than investing on the latest data and analytics software; it also requires cultural and organizational change.
Learn how industry leaders do it, register for our Best Practices Webinar!
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Topics:
bi-on-hadoop,
culture,
Analytics,
BI on Big Data,
data driven
While it may be tempting to focus our efforts only on self-service BI in terms of security and access control mechanisms, it is important to also place emphasis on economies to achieve success. When an enterprise develops a self-service BI environment, it undoubtedly means that their IT team adopts the role of a service provider. Data and services become available to internal business users for a price. What are these hidden costs?
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Topics:
Business Intelligence,
Big Data,
BI,
Data,
BI on Big Data
We Told You It Would Be Cloudy
You have probably already heard all about it, read all about it and know all about it, but if you are anything like me, (or Einstein) you have already figured out that the more we learn about BI on Big Data the more we realize how little we know. Or, do we?
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Topics:
Hadoop,
bi-on-hadoop,
Analytics,
BI on Big Data,
6.0,
Amazon,
AWS,
RedShift
The Forecast Calls for Cloudy Weather
You don’t have to be a clairvoyant to know that there is an ever-increasing trend in cloud adoption among start-ups and enterprises alike. In the world of Big Data, the past few years have shown a significant increase in cloud adoption. While Amazon initially led the way with cloud data products - with Amazon Elastic MapReduce (EMR) for Hadoop and Redshift for data warehousing - the past 12 months have seen new entrants on the scene.
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Topics:
Hadoop,
bi-on-hadoop,
Analytics,
BI on Big Data,
6.0,
azure,
HDInsight,
Microsoft
Is it October already?
It’s hard to believe that October is here. It feels like only a few days ago that we released AtScale 5.0 and AtScale 5.5. Both releases contained a number of great new features that I was excited to share with the Big Data and Business Intelligence communities. Although I may be a little biased, I really do believe that the release of AtScale 6.0 marks one of the biggest releases in the history of the company.
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Topics:
Hadoop,
Tableau,
bi-on-hadoop,
Analytics,
BI on Big Data,
Google BigQuery,
BigQuery,
6.0
Despite the challenges associated with data warehousing, enterprise IT leaders have accepted it as a necessary evil of deriving value from information within Hadoop and other Big Data ecosystems. How much does it cost to create data warehouses or datamarts that extract data out of Hadoop? Is there a better way to do BI on Big Data?!
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Topics:
Hadoop,
bi-on-hadoop,
Analytics,
BI on Big Data
Industry leaders know that their challenges with data analytics are spread across 4 areas: confirmation (‘the things they know they know’); intuition (‘the things they don’t know they know’); inspection (‘the things they know they don’t know’); and revelation (‘the things they don’t know they don’t know).
This last category is often the most tragic for organizations. Luckily, we now have helpful resources from Tom Davenport's latest webinar on Data Strategy to key research data points on chief data executive's priorities.
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Topics:
Chief Data Officer,
Analytics,
BI on Big Data,
CDO,
Data Strategy
The rapidly exploding demand for business intelligence on big data is nothing new - this trend is clearly indicated in the latest Big Data Maturity surveys (2015 and 2016). As shown in the graphic below, 75% of respondents are planning on deploying BI workloads on their big data platforms (with 73% of respondents already with some BI use cases deployed).
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Topics:
Hadoop,
hive,
bi-on-hadoop,
Analytics,
BI on Big Data,
druid
Every once in awhile, the ultimate question comes up: "What is the best analysis tool for BI on Hadoop?!" AtScale is not in the business of favoring one tool versus the other. We are in the business of making all of them work. There are indeed many reasons why business users and IT departments choose particular analysis tools. Here are a few things to consider.
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Topics:
Hadoop,
bi-on-hadoop,
Analytics,
BI on Big Data
