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Big Data

Key Considerations for Executing a Successful M&A Data Migration or Carve-Out




Click to learn more about author Steele Arbeeny

Mergers, acquisitions, and divestitures
are just as much of an undertaking for a CIO as they are for a CFO; they are
impactful on both the business and technology side. Determining which SAP
systems and data sets to migrate, integrate, or carve-out as part of the deal —
and then executing on those migrations or carve-outs — can be costly, lengthy,
and incredibly complex processes, which in turn impacts your overall timeline.
Missteps in the data migration process can result in unnecessary technical
debt, potential Transition Services Agreement penalties, and even delays in achieving
your final goals for the project. 

There are some key considerations that I would recommend to companies undergoing mergers, acquisitions, or divestitures when it comes to their data migration needs. Chief among those considerations is the need to build automation into the heart of your migration or carve-out strategies and why aligning with the right software-driven partner is integral for executing a data migration or carve-out that stays on track and achieves overall timelines and goals.

Create a Clear Plan of Action

Mergers, acquisitions, and
divestitures are incredibly complex processes. Obviously, no business
undertakes one without first outlining a clear plan of action and a timeline
for that plan to proceed along. But it’s crucial that that plan also prioritizes
the data migration side of the operation; it can’t just be a business-facing
process. Data migrations and carve-outs are among the most daunting tasks that
come with executing a merger, acquisition, or divestiture — so getting it right
is critical to accomplishing the broader mission at hand.

While every company’s situation is
different, there are a few key questions that businesses undergoing a merger,
acquisition, or divestiture need to ask themselves to ensure their data needs
aren’t being overlooked:

  • Do we need to
    integrate the company we just bought into our ERP systems? In the case of a
    divestiture: Do we need to identify and carve out data from our systems?
  • Does the company we’re
    acquiring use SAP or another kind of ERP? Do both companies already share the
    same kind of ERP?
  • What regulatory issues
    may come up that could lengthen, halt, or delay the process? Are there any
    potential TSA compliance hurdles that we might come up against?

    • One area to consider
      is sales overlaps. With a 20 percent overlap from balance sheet to balance
      sheet, this can present a significant potential regulatory obstacle.
  • How quickly do we need
    the data migration or carve-out done?

While these may seem like fundamental
first steps, they’re crucial ones. Without a clear outline of your data needs,
you could end up in a situation where a merger, acquisition, or divestiture
results in the new company taking on excessive levels of technical debt or
violating regulatory compliance — which itself carries a whole host of new
problems with which to deal.

Putting Automation Front and Center

Whether you’re integrating or carving out data, the process is incredibly labor-intensive and rife with repetitive tasks. More than that, each decision to be made carries potentially far-reaching consequences for everything from data history preservation and master data relevance to security and compliance. In other words, getting it right the first time is business-critical.

This is all the more the reason why
automation needs to be treated as an integral part of these processes.
Automating data migrations or carve-outs ensures that the volume of menial
tasks is being executed both quickly and painlessly while leaving the more
weighted choices to be done manually. Automation ensures decision-makers are
essentially only spending their time and resources on the tasks that most
require their input — all of which enables IT teams to best allocate and
prioritize their resources for performing even the most challenging carve-out
or migration plans.

This also comes in handy in the
aftermath of the merger, where automation can speed up post-merger/acquisition
integration projects, both accelerating how quickly and seamlessly the
migration can take hold while providing a new level of insight and control over
the process that can’t otherwise be achieved through traditional, manual

Executing with Minimal Business

After building a plan of action
and wrapping it around an automation-driven strategy, the next consideration
ultimately turns to the go-live date: Can your business handle a disruption
that lasts longer than a weekend? How quickly do you need to execute the data
migration, or carve-out, to avoid lengthy disruptions in your business
operations? Just how long is too long?

This might be the last step in the
process, but it’s no less critical. Being able to carry out your new data
migration or carve-out with minimal downtime or disruptions to the business is
essentially the first proving ground of how successful your new merger,
acquisition, or divestiture will be. To that end, businesses undergoing these
transformations need to ensure they’ve aligned themselves with the right
software partner ahead of time. Successful data migrations and carve-outs are
integral to the success of the newly merged or divested company and key to
averting the technical debt or TSA violations that can otherwise knock you off
track. Getting that done on time and in line with your goals requires getting
off on the right foot with the right partner.

With so much at stake, businesses
undergoing a merger, acquisition, or divestiture need nothing less than a
predictable process for executing their data migration and carve-out needs — a
software-driven, end-to-end, automated process that is predictable in its
speed, efficiency, and success rate in delivering on your goals within your


Big Data

Certifications To Drive Your Big Data Professional Career




In the modern age, one of the most valuable assets a business possesses is the data it generates. Business data is an unparalleled source to derive a competitive advantage over other businesses operating within your niche or industry segment. It is so valuable, that businesses spend billions each year on data security and privacy measures, both to protect their customers as well as the valuable data itself.
However, raw data in itself does not offer much value. Given the large volumes of data that businesses produce on a daily basis, simply managing it can be a huge task, let alone analyzing it to draw the correct conclusions. This is where big data professionals come in.


How to Become a Certified Big Data Professional?

The larger a business is, the more data it likely generates. For enterprise-level businesses, this data can become so extensive that simple inference tools aren’t enough to draw valuable information from it. The vast quantities of data are full of hidden trends, process efficiency indicators, sales volume fluctuation, and even customer behavior. However, for an average-Joe, it may be virtually impossible to use it in a significant way. After all, it’s not as simple as figuring out how to get Spectrum TV.

But a certified big data professional has all the expertise and knowledge needed to make constructive use of the data that businesses accumulate. This is one of the reasons why data scientists are in such demand in the business world. Using sophisticated statistical and analytical techniques, big data professionals are able to correctly predict trends and identify areas of improvement. This helps businesses improve their overall process efficiency and position themselves to take advantage of emerging trends. If you’re thinking of dipping into the big data profession, here are a few certifications that will prove useful along the way:

1. Microsoft MCSE Data Management and Analytics.

2. Cloudera Data Professional Certification

3. Hortonworks Hadoop

4. EMC Data Science and Big Data Analytics

Here’s how these certifications can help you get closer to your goal of becoming a successful big data professional.


Microsoft MCSE Data Management and Analytics

Microsoft is one of the oldest and most iconic tech companies in modern history. So it makes sense that they have developed specialized tools and certifications to help professionals who work with big data in a business setting. The company’s MCSE program is designed to help individuals become proficient at using various Microsoft tools and software. Successfully completing the program means you become a certified big data professional in terms of:

  • SQL database administration.
  • Development
  • Machine learning.
  • Business intelligence reporting.

The program hones your skills so you can have demonstrable expertise in SQL, building data solutions for large-scale enterprises, and deriving intelligence from business data. Any tech-savvy employer will jump at the chance to add you to their team.


Cloudera Data Professional Certification

If you want to learn how to create and work on big data pipelines, the Cloudera certification is something you should seriously consider. The company has established itself as an authority on Hadoop, and getting certified by it is one of the most useful endorsements you can have in the big data profession. It lists a range of certifications that offer proficiency in Apache Spark, Hadoop Development, and Hadoop Administration.

Hortonworks Hadoop

Speaking of authorities in the Hadoop domain, Hortonworks is a commercial vendor that has been offering customized Hadoop tools and solutions to enterprises for some time now. These services have a broad range of applications in data management and intelligence. The company now also offers various certifications for Hadoop, including Hadoop development and administration as well as Spark development among others. The certification is great for building your skillset in:

  • Data ingestion.
  • Data transformation.
  • Analyzing big data.


EMC Data Science and Big Data Analytics

EMC offers certifications designed to build and increase proficiency in various specific aspects of the Hadoop environment. It covers a variety of bases, including Pig, Hive, and HBase. It also pays a lot of attention to delivering knowledge on data visualization, NLP, and even logistic regression. In addition, the certification will grant you proficiency in data analytics, data science roles, building complex data models, and evaluating it for results.

Big data professionals are needed by virtually every enterprise-level firm in the world. They are needed to analyze complex information, from measuring customer satisfaction ratios on the Spectrum cable phone number to identifying process inefficiencies in manufacturing. With an increased dependency on data to outperform and outclass the competition, businesses are willing to pay handsomely for this niche skillset. A professional certification can greatly increase your chances of getting lucrative employment in the field.

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Big Data

Teen banking app Step reaches for the stars to raise $50 million




By Anna Irrera

LONDON (Reuters) – Teen banking app Step has raised $50 million (37.4 million pounds) from investors led by Coatue Management alongside celebrities such as singer Justin Timberlake, influencer Charli D’Amelio and former quarterback Eli Manning.

Step, which offers teenagers a bank account connected to a secured spending card and peer-to-peer payments, also said it had secured funding from existing backers including Stripe, Will Smith’s Dreamers VC, CrossLink Capital and Collaborative Fund.

San Francisco-based Step allows parents to view balances and real-time activity, add money to their teens’ accounts and manage and freeze cards. It does not charge fees but makes money from card interchange.

Other stars involved in the fundraising included The Chainsmokers, Kelvin Beachum, Larry Fitzgerald and Andre Iguodala, Step said in a statement on Wednesday.

The startup, which has attracted more than 500,000 users since launching two months ago, will use the funding to grow the team and invest in its technology, its chief executive CJ MacDonald told Reuters in a video call.

“We are making sure we are building scalable solutions and are able to handle the growth,” MacDonald said.

Step is one of several new banking apps focused on children and teens in the U.S., as companies seek to capitalise on a global surge in digital payments and ecommerce. It rivals products from companies including Greenlight, Copper and JPMorgan Chase & Co.

Such companies say they aim to make it easier for parents and their children to transact in an increasingly cashless economy, while providing more modern financial education tools.

“As a person who hasn’t always had financial stability, and made many mistakes in that arena as a young man, I know the importance of financial education and having access to economic platforms that can work for everyone,” Smith, who is a co-founder of Dreamers VC, said in a statement.

(Reporting by Anna Irrera; Editing by Alexander Smith)

Image Credit: Reuters


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Big Data

Intel’s Habana starts to chip away at Nvidia in cloud with AWS deal




By Steven Scheer

JERUSALEM (Reuters) – Intel Corp’s Habana Labs business said on Wednesday it would take time to gain market share from Nvidia in cloud and data centre computing but its deal this week with Amazon Web Services (AWS) was a solid first step.

Intel in December bought Israel-based artificial intelligence firm Habana for about $2 billion, seeking to expand its AI portfolio to bolster its data-centre business.

Habana’s Gaudi AI training processor, launched in June 2019, has faster processing speeds to compete with similar products from Intel rival Nvidia.

“We have to realise that we’re starting from zero and Nvidia is 100%,” said Eitan Medina, Habana’s chief business officer, who said that having AWS as its first customer was very important.

“The uphill battle or the process of taking market share has to go through convincing end developers to try it out,” he told reporters. “We are making the dent at the most important place. We’re starting with a very big guy that has the longest experience … It will take time but I believe we’re on the right path.”

Medina declined to comment on whether Habana was negotiating other deals.

Habana on Tuesday said its Gaudi processors will power AWS’s Amazon Elastic Compute Cloud “instances” for machine learning workloads, in Habana’s first deal for its Gaudi chips.

Amazon is seeing growing demand for its cloud tools during the coronavirus pandemic. These chips, Intel said, would give 40% better price performance than current graphics processing.

Medina said that the advantages of Gaudi AI chips were efficiency and allowing for lower capital and operating expenses that in turn could give AWS and others the ability to lower prices for customers for server time.

“We are now starting so it will depend on the combination of how we will execute and how important is it for users to lower their cost and to have alternatives to GPUs (graphics processing units),” Medina said. “Our total available market is 100% of AI.”

(Reporting by Steven Scheer. Editing by Jane Merriman)

Image Credit: Reuters


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Big Data

U.S judge hearing Google case rejects government’s protective order request




WASHINGTON (Reuters) – The federal judge hearing the U.S. Justice Department’s antitrust lawsuit against Alphabet’s Google urged the government on Wednesday to narrow the definition of “highly sensitive” information as he considered arguments on which of Google’s lawyers would be able to see evidence produced by other companies.

U.S. District Judge Amit Mehta asked the two sides to produce a revised protective order by Dec. 14 while companies, like Apple Inc or AT&T Inc, which produced the information, would have until Dec. 15 to file on the matter.

The Justice Department, which sued the search and advertising giant in October, put at the core of its antitrust case the billions of dollars that Google paid to be the default search engine on Apple’s iPhones. Apple noted in its filing that sensitive data was used to write the complaint.

(Reporting by Diane Bartz; editing by Jonathan Oatis)

Image Credit: Reuters


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